load("vcomball20210601.Rda")
d <- vcomball
#load("vsiteid20210601.Rda")
new.d <- data.frame(matrix(ncol=0, nrow=nrow(d)))
new.d.1 <- data.frame(matrix(ncol=0, nrow=nrow(d)))
siteid <- as.factor(trimws(d[,"siteid"]))
#new.d.n <- data.frame(new.d.n, siteid) # keep NAACCR coding
# NEED REGISTRY NAMES!!
#replace number with names
levels(siteid)[levels(siteid)=="80"] <- "Los Angeles County.80"
levels(siteid)[levels(siteid)=="30"] <- "Northern CA.30"
levels(siteid)[levels(siteid)=="10"] <- "Greater CA.10"
levels(siteid)[levels(siteid)=="60"] <- "Detroit.60"
levels(siteid)[levels(siteid)=="40"] <- "Louisiana.40"
levels(siteid)[levels(siteid)=="20"] <- "Georgia.20"
levels(siteid)[levels(siteid)=="61"] <- "Michigan.61"
new.d <- data.frame(new.d, siteid)
new.d <- apply_labels(new.d, siteid = "Site ID")
new.d.1 <- data.frame(new.d.1, siteid)
#cro(new.d$siteid) # this is pretty but doesn't show NAs
#summary(new.d$siteid)
#Using kable function to form a nice table
siteid_count<-count(new.d$siteid)
colnames(siteid_count)<- c("Registry", "Total")
kable(siteid_count, format = "simple", align = 'l', caption = "Overview of all Registries")
| Registry | Total |
|---|---|
| Greater CA.10 | 315 |
| Georgia.20 | 1754 |
| Northern CA.30 | 210 |
| Louisiana.40 | 585 |
| Detroit.60 | 356 |
| Michigan.61 | 16 |
| Los Angeles County.80 | 321 |
surveyid <- as.factor(d[,"surveyid"])
isDup <- duplicated(surveyid)
numDups <- sum(isDup)
dups <- surveyid[isDup]
new.d <- data.frame(new.d, surveyid)
new.d <- apply_labels(new.d, surveyid = "Survey ID")
print(paste("Number of duplicates:", numDups))
## [1] "Number of duplicates: 6"
print("The following are duplicated IDs:")
## [1] "The following are duplicated IDs:"
print(dups)
## [1] 101079 100849 300631 200312 201605 211392
## 3551 Levels: 100037 100050 100059 100061 100064 100072 100073 ... 991774
print("Number of NAs:")
## [1] "Number of NAs:"
print(sum(is.na(new.d$surveyid)))
## [1] 0
locationname <- as.factor(d[,"locationname"])
new.d <- data.frame(new.d, locationname)
new.d <- apply_labels(new.d, locationname = "Recruitment Location")
#To get the number of each registry
locationname_count<-count(new.d$locationname)
colnames(locationname_count)<- c("Location", "Total")
#To get freq of each registry
locationname_freq1<-table(new.d$locationname)
locationname_freq<-as.data.frame(round(prop.table(locationname_freq1),3))
colnames(locationname_freq)<- c("Location", "Freq")
#Merge them by "Location"
result<-merge(locationname_count,locationname_freq,by="Location", sort=F)
#Create a NICE table
kable(result, format = "simple", align = 'l', caption = "Overview of Registry delivery location")
| Location | Total | Freq |
|---|---|---|
| Detroit | 292 | 0.082 |
| Georgia | 1839 | 0.517 |
| Greater Bay | 210 | 0.059 |
| Greater California | 315 | 0.089 |
| Los Angeles | 321 | 0.090 |
| Louisiana | 500 | 0.141 |
| Virtual | 80 | 0.022 |
respondid <- as.factor(d[,"respondid"])
#remove NAs in respondid in order to avoid showing NAs in duplicated values
respondid_rm<-respondid[!is.na(respondid)]
isDup <- duplicated(respondid_rm)
numDups <- sum(isDup)
dups <- respondid_rm[isDup]
new.d <- data.frame(new.d, respondid)
new.d <- apply_labels(new.d, respondid = "RESPOND ID")
print(paste("Number of duplicates:", numDups))
## [1] "Number of duplicates: 14"
print("The following are duplicated IDs:")
## [1] "The following are duplicated IDs:"
print(dups)
## [1] 61100276 10100813 10100628 30100177 30100278 30100172 20100653 40102145
## [9] 10101130 61100327 40100589 20100647 20100647 20103912
## 3543 Levels: 10100003 10100012 10100023 10100024 10100027 10100029 ... 80101425
print("Number of NAs:")
## [1] "Number of NAs:"
print(sum(is.na(new.d$respondid)))
## [1] 0
st_css()
methodology <- as.factor(d[,"methodology"])
levels(methodology) <- list(Paper="P",
Online="O")
methodology <- ordered(methodology, c("Paper", "Online"))
new.d <- data.frame(new.d, methodology)
new.d <- apply_labels(new.d, methodology = "Methodology for Survey Completion")
temp.d <- data.frame (new.d, methodology)
result<-questionr::freq(temp.d$methodology, total = TRUE)
kable(result, format = "simple", align = 'l')
| n | % | val% | |
|---|---|---|---|
| Paper | 2976 | 83.7 | 83.7 |
| Online | 581 | 16.3 | 16.3 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Paper | 321 | 100 | 100 |
| Online | 0 | 0 | 0 |
| Total | 321 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| Paper | 168 | 80 | 80 |
| Online | 42 | 20 | 20 |
| Total | 210 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| Paper | 275 | 87.3 | 87.3 |
| Online | 40 | 12.7 | 12.7 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Paper | 281 | 78.9 | 78.9 |
| Online | 75 | 21.1 | 21.1 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Paper | 553 | 94.5 | 94.5 |
| Online | 32 | 5.5 | 5.5 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Paper | 1366 | 77.9 | 77.9 |
| Online | 388 | 22.1 | 22.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Paper | 12 | 75 | 75 |
| Online | 4 | 25 | 25 |
| Total | 16 | 100 | 100 |
# a1month
a1month <- as.factor(d[,"a1month"])
new.d <- data.frame(new.d, a1month)
new.d <- apply_labels(new.d, a1month = "Month Diagnosed")
temp.d <- data.frame (new.d, a1month)
result<-questionr::freq(temp.d$a1month, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A1:month diagnosed")
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.0 | 0.0 |
| 0* | 1 | 0.0 | 0.0 |
| 1 | 227 | 6.4 | 6.4 |
| 10 | 268 | 7.5 | 7.5 |
| 11 | 215 | 6.0 | 6.0 |
| 12 | 168 | 4.7 | 4.7 |
| 18 | 1 | 0.0 | 0.0 |
| 2 | 227 | 6.4 | 6.4 |
| 22 | 1 | 0.0 | 0.0 |
| 25 | 2 | 0.1 | 0.1 |
| 3 | 278 | 7.8 | 7.8 |
| 4 | 284 | 8.0 | 8.0 |
| 48 | 1 | 0.0 | 0.0 |
| 5 | 264 | 7.4 | 7.4 |
| 6 | 426 | 12.0 | 12.0 |
| 7 | 258 | 7.3 | 7.3 |
| 8 | 236 | 6.6 | 6.6 |
| 9 | 221 | 6.2 | 6.2 |
| “NA” | 478 | 13.4 | 13.4 |
| Total | 3557 | 100.0 | 100.0 |
#count<-as.data.frame(table(new.d$a1month))
#colnames(count)<- c("a1month", "Total")
#freq1<-table(new.d$a1month)
#freq<-as.data.frame(round(prop.table(freq1),3))
#colnames(freq)<- c("a1month", "Freq")
#result<-merge(count, freq,by="a1month",sort=F)
#kable(result, format = "simple", align = 'l', caption = "A1:month diagnosed")
#a1year
tmp<-d[,"a1year"]
tmp[tmp=="15"]<-"2015"
a1year <- as.factor(tmp)
#levels(a1year)[levels(a1year)=="15"] <- "2015"
#a1year[a1year=="15"] <- "2015" # change "15" to "2015"
#a1year <- as.Date(a1year, format = "%Y")
#a1year <- relevel(a1year, ref="1914")
new.d <- data.frame(new.d, a1year)
new.d <- apply_labels(new.d, a1year = "Year Diagnosed")
temp.d <- data.frame (new.d, a1year)
result<-questionr::freq(temp.d$a1year, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A1:year diagnosed")
| n | % | val% | |
|---|---|---|---|
| 1914 | 1 | 0.0 | 0.0 |
| 1915 | 3 | 0.1 | 0.1 |
| 1916 | 7 | 0.2 | 0.2 |
| 1917 | 9 | 0.3 | 0.3 |
| 1918 | 3 | 0.1 | 0.1 |
| 1937 | 1 | 0.0 | 0.0 |
| 1941 | 1 | 0.0 | 0.0 |
| 1943 | 1 | 0.0 | 0.0 |
| 1944 | 1 | 0.0 | 0.0 |
| 1945 | 2 | 0.1 | 0.1 |
| 1946 | 1 | 0.0 | 0.0 |
| 1947 | 2 | 0.1 | 0.1 |
| 1948 | 2 | 0.1 | 0.1 |
| 1949 | 2 | 0.1 | 0.1 |
| 1950 | 3 | 0.1 | 0.1 |
| 1951 | 2 | 0.1 | 0.1 |
| 1952 | 3 | 0.1 | 0.1 |
| 1953 | 1 | 0.0 | 0.0 |
| 1954 | 2 | 0.1 | 0.1 |
| 1955 | 2 | 0.1 | 0.1 |
| 1956 | 1 | 0.0 | 0.0 |
| 1963 | 2 | 0.1 | 0.1 |
| 1965 | 1 | 0.0 | 0.0 |
| 1987 | 1 | 0.0 | 0.0 |
| 1989 | 1 | 0.0 | 0.0 |
| 1990 | 1 | 0.0 | 0.0 |
| 1993 | 3 | 0.1 | 0.1 |
| 1994 | 1 | 0.0 | 0.0 |
| 1995 | 2 | 0.1 | 0.1 |
| 1996 | 1 | 0.0 | 0.0 |
| 1997 | 1 | 0.0 | 0.0 |
| 1998 | 4 | 0.1 | 0.1 |
| 1999 | 4 | 0.1 | 0.1 |
| 20 | 1 | 0.0 | 0.0 |
| 2000 | 1 | 0.0 | 0.0 |
| 2001 | 1 | 0.0 | 0.0 |
| 2002 | 1 | 0.0 | 0.0 |
| 2003 | 2 | 0.1 | 0.1 |
| 2004 | 6 | 0.2 | 0.2 |
| 2005 | 6 | 0.2 | 0.2 |
| 2006 | 5 | 0.1 | 0.1 |
| 2007 | 4 | 0.1 | 0.1 |
| 2008 | 8 | 0.2 | 0.2 |
| 2009 | 7 | 0.2 | 0.2 |
| 2010 | 17 | 0.5 | 0.5 |
| 2011 | 13 | 0.4 | 0.4 |
| 2012 | 29 | 0.8 | 0.8 |
| 2013 | 63 | 1.8 | 1.8 |
| 2014 | 177 | 5.0 | 5.0 |
| 2015 | 860 | 24.2 | 24.2 |
| 2016 | 1157 | 32.5 | 32.5 |
| 2017 | 551 | 15.5 | 15.5 |
| 2018 | 200 | 5.6 | 5.6 |
| 2019 | 52 | 1.5 | 1.5 |
| 2020 | 22 | 0.6 | 0.6 |
| 2021 | 5 | 0.1 | 0.1 |
| 615 | 1 | 0.0 | 0.0 |
| “NA” | 296 | 8.3 | 8.3 |
| Total | 3557 | 100.0 | 100.0 |
#a1not
# 1=I have NEVER had prostate cancer
# 2=I HAVE or HAVE HAD prostate cancer
# (paper survey only had a bubble for “never had” so value set to 2 if bubble not marked)"
a1not <- as.factor(d[,"a1not"])
levels(a1not) <- list(NEVER_had_ProstateCancer="1",
HAVE_had_ProstateCancer="2")
new.d <- data.frame(new.d, a1not)
new.d <- apply_labels(new.d, a1not = "Not Diagnosed")
temp.d <- data.frame (new.d, a1not)
result<-questionr::freq(temp.d$a1not, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A1:not diagnosed")
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 10 | 0.3 | 0.3 |
| HAVE_had_ProstateCancer | 3547 | 99.7 | 99.7 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.3 | 0.3 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 25 | 7.8 | 7.8 |
| 10 | 22 | 6.9 | 6.9 |
| 11 | 13 | 4.0 | 4.0 |
| 12 | 12 | 3.7 | 3.7 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 13 | 4.0 | 4.0 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 3 | 20 | 6.2 | 6.2 |
| 4 | 21 | 6.5 | 6.5 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 25 | 7.8 | 7.8 |
| 6 | 22 | 6.9 | 6.9 |
| 7 | 15 | 4.7 | 4.7 |
| 8 | 18 | 5.6 | 5.6 |
| 9 | 13 | 4.0 | 4.0 |
| “NA” | 101 | 31.5 | 31.5 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 0 | 0.0 | 0.0 |
| 1916 | 0 | 0.0 | 0.0 |
| 1917 | 0 | 0.0 | 0.0 |
| 1918 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 0 | 0.0 | 0.0 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 0 | 0.0 | 0.0 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 0 | 0.0 | 0.0 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 0 | 0.0 | 0.0 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 1 | 0.3 | 0.3 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 0 | 0.0 | 0.0 |
| 1999 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 0 | 0.0 | 0.0 |
| 2004 | 0 | 0.0 | 0.0 |
| 2005 | 0 | 0.0 | 0.0 |
| 2006 | 1 | 0.3 | 0.3 |
| 2007 | 0 | 0.0 | 0.0 |
| 2008 | 2 | 0.6 | 0.6 |
| 2009 | 1 | 0.3 | 0.3 |
| 2010 | 1 | 0.3 | 0.3 |
| 2011 | 0 | 0.0 | 0.0 |
| 2012 | 0 | 0.0 | 0.0 |
| 2013 | 5 | 1.6 | 1.6 |
| 2014 | 8 | 2.5 | 2.5 |
| 2015 | 85 | 26.5 | 26.5 |
| 2016 | 122 | 38.0 | 38.0 |
| 2017 | 64 | 19.9 | 19.9 |
| 2018 | 19 | 5.9 | 5.9 |
| 2019 | 0 | 0.0 | 0.0 |
| 2020 | 1 | 0.3 | 0.3 |
| 2021 | 0 | 0.0 | 0.0 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 11 | 3.4 | 3.4 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 0 | 0 | 0 |
| HAVE_had_ProstateCancer | 321 | 100 | 100 |
| Total | 321 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 16 | 7.6 | 7.6 |
| 10 | 21 | 10.0 | 10.0 |
| 11 | 13 | 6.2 | 6.2 |
| 12 | 5 | 2.4 | 2.4 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 18 | 8.6 | 8.6 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 3 | 21 | 10.0 | 10.0 |
| 4 | 11 | 5.2 | 5.2 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 14 | 6.7 | 6.7 |
| 6 | 22 | 10.5 | 10.5 |
| 7 | 13 | 6.2 | 6.2 |
| 8 | 15 | 7.1 | 7.1 |
| 9 | 11 | 5.2 | 5.2 |
| “NA” | 30 | 14.3 | 14.3 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 0 | 0.0 | 0.0 |
| 1916 | 1 | 0.5 | 0.5 |
| 1917 | 0 | 0.0 | 0.0 |
| 1918 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 0 | 0.0 | 0.0 |
| 1946 | 1 | 0.5 | 0.5 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 0 | 0.0 | 0.0 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 1 | 0.5 | 0.5 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 0 | 0.0 | 0.0 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 0 | 0.0 | 0.0 |
| 1999 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 0 | 0.0 | 0.0 |
| 2004 | 0 | 0.0 | 0.0 |
| 2005 | 0 | 0.0 | 0.0 |
| 2006 | 1 | 0.5 | 0.5 |
| 2007 | 0 | 0.0 | 0.0 |
| 2008 | 0 | 0.0 | 0.0 |
| 2009 | 0 | 0.0 | 0.0 |
| 2010 | 0 | 0.0 | 0.0 |
| 2011 | 1 | 0.5 | 0.5 |
| 2012 | 3 | 1.4 | 1.4 |
| 2013 | 2 | 1.0 | 1.0 |
| 2014 | 8 | 3.8 | 3.8 |
| 2015 | 62 | 29.5 | 29.5 |
| 2016 | 62 | 29.5 | 29.5 |
| 2017 | 35 | 16.7 | 16.7 |
| 2018 | 6 | 2.9 | 2.9 |
| 2019 | 2 | 1.0 | 1.0 |
| 2020 | 1 | 0.5 | 0.5 |
| 2021 | 0 | 0.0 | 0.0 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 24 | 11.4 | 11.4 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 0 | 0 | 0 |
| HAVE_had_ProstateCancer | 210 | 100 | 100 |
| Total | 210 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 18 | 5.7 | 5.7 |
| 10 | 27 | 8.6 | 8.6 |
| 11 | 21 | 6.7 | 6.7 |
| 12 | 17 | 5.4 | 5.4 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 19 | 6.0 | 6.0 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 3 | 20 | 6.3 | 6.3 |
| 4 | 26 | 8.3 | 8.3 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 23 | 7.3 | 7.3 |
| 6 | 46 | 14.6 | 14.6 |
| 7 | 24 | 7.6 | 7.6 |
| 8 | 22 | 7.0 | 7.0 |
| 9 | 19 | 6.0 | 6.0 |
| “NA” | 33 | 10.5 | 10.5 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 1 | 0.3 | 0.3 |
| 1916 | 0 | 0.0 | 0.0 |
| 1917 | 1 | 0.3 | 0.3 |
| 1918 | 1 | 0.3 | 0.3 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 1 | 0.3 | 0.3 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 0 | 0.0 | 0.0 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 1 | 0.3 | 0.3 |
| 1951 | 1 | 0.3 | 0.3 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 0 | 0.0 | 0.0 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 1 | 0.3 | 0.3 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 0 | 0.0 | 0.0 |
| 1999 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 1 | 0.3 | 0.3 |
| 2003 | 0 | 0.0 | 0.0 |
| 2004 | 1 | 0.3 | 0.3 |
| 2005 | 2 | 0.6 | 0.6 |
| 2006 | 0 | 0.0 | 0.0 |
| 2007 | 0 | 0.0 | 0.0 |
| 2008 | 0 | 0.0 | 0.0 |
| 2009 | 1 | 0.3 | 0.3 |
| 2010 | 4 | 1.3 | 1.3 |
| 2011 | 0 | 0.0 | 0.0 |
| 2012 | 1 | 0.3 | 0.3 |
| 2013 | 4 | 1.3 | 1.3 |
| 2014 | 18 | 5.7 | 5.7 |
| 2015 | 91 | 28.9 | 28.9 |
| 2016 | 123 | 39.0 | 39.0 |
| 2017 | 26 | 8.3 | 8.3 |
| 2018 | 7 | 2.2 | 2.2 |
| 2019 | 3 | 1.0 | 1.0 |
| 2020 | 1 | 0.3 | 0.3 |
| 2021 | 0 | 0.0 | 0.0 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 25 | 7.9 | 7.9 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 0 | 0 | 0 |
| HAVE_had_ProstateCancer | 315 | 100 | 100 |
| Total | 315 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 26 | 7.3 | 7.3 |
| 10 | 21 | 5.9 | 5.9 |
| 11 | 16 | 4.5 | 4.5 |
| 12 | 19 | 5.3 | 5.3 |
| 18 | 1 | 0.3 | 0.3 |
| 2 | 18 | 5.1 | 5.1 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 3 | 33 | 9.3 | 9.3 |
| 4 | 27 | 7.6 | 7.6 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 19 | 5.3 | 5.3 |
| 6 | 50 | 14.0 | 14.0 |
| 7 | 28 | 7.9 | 7.9 |
| 8 | 25 | 7.0 | 7.0 |
| 9 | 26 | 7.3 | 7.3 |
| “NA” | 47 | 13.2 | 13.2 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 1 | 0.3 | 0.3 |
| 1915 | 1 | 0.3 | 0.3 |
| 1916 | 1 | 0.3 | 0.3 |
| 1917 | 1 | 0.3 | 0.3 |
| 1918 | 1 | 0.3 | 0.3 |
| 1937 | 1 | 0.3 | 0.3 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 0 | 0.0 | 0.0 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 1 | 0.3 | 0.3 |
| 1948 | 1 | 0.3 | 0.3 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 1 | 0.3 | 0.3 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 1 | 0.3 | 0.3 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 2 | 0.6 | 0.6 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 1 | 0.3 | 0.3 |
| 1999 | 1 | 0.3 | 0.3 |
| 20 | 1 | 0.3 | 0.3 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 1 | 0.3 | 0.3 |
| 2004 | 1 | 0.3 | 0.3 |
| 2005 | 1 | 0.3 | 0.3 |
| 2006 | 0 | 0.0 | 0.0 |
| 2007 | 1 | 0.3 | 0.3 |
| 2008 | 0 | 0.0 | 0.0 |
| 2009 | 0 | 0.0 | 0.0 |
| 2010 | 2 | 0.6 | 0.6 |
| 2011 | 3 | 0.8 | 0.8 |
| 2012 | 4 | 1.1 | 1.1 |
| 2013 | 17 | 4.8 | 4.8 |
| 2014 | 26 | 7.3 | 7.3 |
| 2015 | 51 | 14.3 | 14.3 |
| 2016 | 66 | 18.5 | 18.5 |
| 2017 | 71 | 19.9 | 19.9 |
| 2018 | 48 | 13.5 | 13.5 |
| 2019 | 11 | 3.1 | 3.1 |
| 2020 | 1 | 0.3 | 0.3 |
| 2021 | 2 | 0.6 | 0.6 |
| 615 | 1 | 0.3 | 0.3 |
| “NA” | 34 | 9.6 | 9.6 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 1 | 0.3 | 0.3 |
| HAVE_had_ProstateCancer | 355 | 99.7 | 99.7 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 37 | 6.3 | 6.3 |
| 10 | 43 | 7.4 | 7.4 |
| 11 | 32 | 5.5 | 5.5 |
| 12 | 26 | 4.4 | 4.4 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 45 | 7.7 | 7.7 |
| 22 | 1 | 0.2 | 0.2 |
| 25 | 1 | 0.2 | 0.2 |
| 3 | 60 | 10.3 | 10.3 |
| 4 | 62 | 10.6 | 10.6 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 54 | 9.2 | 9.2 |
| 6 | 80 | 13.7 | 13.7 |
| 7 | 48 | 8.2 | 8.2 |
| 8 | 29 | 5.0 | 5.0 |
| 9 | 40 | 6.8 | 6.8 |
| “NA” | 27 | 4.6 | 4.6 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 1 | 0.2 | 0.2 |
| 1916 | 0 | 0.0 | 0.0 |
| 1917 | 3 | 0.5 | 0.5 |
| 1918 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 1 | 0.2 | 0.2 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 0 | 0.0 | 0.0 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 0 | 0.0 | 0.0 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 0 | 0.0 | 0.0 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 0 | 0.0 | 0.0 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 1 | 0.2 | 0.2 |
| 1999 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 0 | 0.0 | 0.0 |
| 2004 | 1 | 0.2 | 0.2 |
| 2005 | 0 | 0.0 | 0.0 |
| 2006 | 0 | 0.0 | 0.0 |
| 2007 | 0 | 0.0 | 0.0 |
| 2008 | 2 | 0.3 | 0.3 |
| 2009 | 0 | 0.0 | 0.0 |
| 2010 | 2 | 0.3 | 0.3 |
| 2011 | 2 | 0.3 | 0.3 |
| 2012 | 2 | 0.3 | 0.3 |
| 2013 | 5 | 0.9 | 0.9 |
| 2014 | 22 | 3.8 | 3.8 |
| 2015 | 98 | 16.8 | 16.8 |
| 2016 | 234 | 40.0 | 40.0 |
| 2017 | 141 | 24.1 | 24.1 |
| 2018 | 37 | 6.3 | 6.3 |
| 2019 | 13 | 2.2 | 2.2 |
| 2020 | 2 | 0.3 | 0.3 |
| 2021 | 0 | 0.0 | 0.0 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 18 | 3.1 | 3.1 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 5 | 0.9 | 0.9 |
| HAVE_had_ProstateCancer | 580 | 99.1 | 99.1 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 1 | 0.1 | 0.1 |
| 1 | 102 | 5.8 | 5.8 |
| 10 | 133 | 7.6 | 7.6 |
| 11 | 120 | 6.8 | 6.8 |
| 12 | 87 | 5.0 | 5.0 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 112 | 6.4 | 6.4 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.1 | 0.1 |
| 3 | 121 | 6.9 | 6.9 |
| 4 | 136 | 7.8 | 7.8 |
| 48 | 1 | 0.1 | 0.1 |
| 5 | 129 | 7.4 | 7.4 |
| 6 | 204 | 11.6 | 11.6 |
| 7 | 130 | 7.4 | 7.4 |
| 8 | 125 | 7.1 | 7.1 |
| 9 | 112 | 6.4 | 6.4 |
| “NA” | 240 | 13.7 | 13.7 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 0 | 0.0 | 0.0 |
| 1916 | 5 | 0.3 | 0.3 |
| 1917 | 4 | 0.2 | 0.2 |
| 1918 | 1 | 0.1 | 0.1 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 1 | 0.1 | 0.1 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 1 | 0.1 | 0.1 |
| 1945 | 1 | 0.1 | 0.1 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 1 | 0.1 | 0.1 |
| 1948 | 1 | 0.1 | 0.1 |
| 1949 | 2 | 0.1 | 0.1 |
| 1950 | 0 | 0.0 | 0.0 |
| 1951 | 1 | 0.1 | 0.1 |
| 1952 | 3 | 0.2 | 0.2 |
| 1953 | 1 | 0.1 | 0.1 |
| 1954 | 2 | 0.1 | 0.1 |
| 1955 | 1 | 0.1 | 0.1 |
| 1956 | 1 | 0.1 | 0.1 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 1 | 0.1 | 0.1 |
| 1989 | 1 | 0.1 | 0.1 |
| 1990 | 1 | 0.1 | 0.1 |
| 1993 | 3 | 0.2 | 0.2 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 2 | 0.1 | 0.1 |
| 1996 | 1 | 0.1 | 0.1 |
| 1997 | 1 | 0.1 | 0.1 |
| 1998 | 2 | 0.1 | 0.1 |
| 1999 | 3 | 0.2 | 0.2 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 1 | 0.1 | 0.1 |
| 2001 | 1 | 0.1 | 0.1 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 1 | 0.1 | 0.1 |
| 2004 | 3 | 0.2 | 0.2 |
| 2005 | 3 | 0.2 | 0.2 |
| 2006 | 3 | 0.2 | 0.2 |
| 2007 | 3 | 0.2 | 0.2 |
| 2008 | 4 | 0.2 | 0.2 |
| 2009 | 5 | 0.3 | 0.3 |
| 2010 | 7 | 0.4 | 0.4 |
| 2011 | 6 | 0.3 | 0.3 |
| 2012 | 17 | 1.0 | 1.0 |
| 2013 | 25 | 1.4 | 1.4 |
| 2014 | 90 | 5.1 | 5.1 |
| 2015 | 472 | 26.9 | 26.9 |
| 2016 | 550 | 31.4 | 31.4 |
| 2017 | 214 | 12.2 | 12.2 |
| 2018 | 83 | 4.7 | 4.7 |
| 2019 | 22 | 1.3 | 1.3 |
| 2020 | 16 | 0.9 | 0.9 |
| 2021 | 3 | 0.2 | 0.2 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 184 | 10.5 | 10.5 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 4 | 0.2 | 0.2 |
| HAVE_had_ProstateCancer | 1750 | 99.8 | 99.8 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 0* | 0 | 0.0 | 0.0 |
| 1 | 3 | 18.8 | 18.8 |
| 10 | 1 | 6.2 | 6.2 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 2 | 12.5 | 12.5 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 2 | 12.5 | 12.5 |
| 22 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 3 | 3 | 18.8 | 18.8 |
| 4 | 1 | 6.2 | 6.2 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 6 | 2 | 12.5 | 12.5 |
| 7 | 0 | 0.0 | 0.0 |
| 8 | 2 | 12.5 | 12.5 |
| 9 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1914 | 0 | 0.0 | 0.0 |
| 1915 | 0 | 0.0 | 0.0 |
| 1916 | 0 | 0.0 | 0.0 |
| 1917 | 0 | 0.0 | 0.0 |
| 1918 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 0 | 0.0 | 0.0 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 0 | 0.0 | 0.0 |
| 1949 | 0 | 0.0 | 0.0 |
| 1950 | 0 | 0.0 | 0.0 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 0 | 0.0 | 0.0 |
| 1953 | 0 | 0.0 | 0.0 |
| 1954 | 0 | 0.0 | 0.0 |
| 1955 | 0 | 0.0 | 0.0 |
| 1956 | 0 | 0.0 | 0.0 |
| 1963 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1987 | 0 | 0.0 | 0.0 |
| 1989 | 0 | 0.0 | 0.0 |
| 1990 | 0 | 0.0 | 0.0 |
| 1993 | 0 | 0.0 | 0.0 |
| 1994 | 0 | 0.0 | 0.0 |
| 1995 | 0 | 0.0 | 0.0 |
| 1996 | 0 | 0.0 | 0.0 |
| 1997 | 0 | 0.0 | 0.0 |
| 1998 | 0 | 0.0 | 0.0 |
| 1999 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 2000 | 0 | 0.0 | 0.0 |
| 2001 | 0 | 0.0 | 0.0 |
| 2002 | 0 | 0.0 | 0.0 |
| 2003 | 0 | 0.0 | 0.0 |
| 2004 | 0 | 0.0 | 0.0 |
| 2005 | 0 | 0.0 | 0.0 |
| 2006 | 0 | 0.0 | 0.0 |
| 2007 | 0 | 0.0 | 0.0 |
| 2008 | 0 | 0.0 | 0.0 |
| 2009 | 0 | 0.0 | 0.0 |
| 2010 | 1 | 6.2 | 6.2 |
| 2011 | 1 | 6.2 | 6.2 |
| 2012 | 2 | 12.5 | 12.5 |
| 2013 | 5 | 31.2 | 31.2 |
| 2014 | 5 | 31.2 | 31.2 |
| 2015 | 1 | 6.2 | 6.2 |
| 2016 | 0 | 0.0 | 0.0 |
| 2017 | 0 | 0.0 | 0.0 |
| 2018 | 0 | 0.0 | 0.0 |
| 2019 | 1 | 6.2 | 6.2 |
| 2020 | 0 | 0.0 | 0.0 |
| 2021 | 0 | 0.0 | 0.0 |
| 615 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| NEVER_had_ProstateCancer | 0 | 0 | 0 |
| HAVE_had_ProstateCancer | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
a2 <- as.factor(d[,"a2"])
levels(a2) <- list(No="1",
Yes="2",
Scantron_Error="*")
a2 <- ordered(a2, c("Yes","No","Scantron_Error"))
new.d <- data.frame(new.d, a2)
new.d <- apply_labels(new.d, a2 = "Month Diagnosed")
temp.d <- data.frame (new.d, a2)
result<-questionr::freq(temp.d$a2, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A2")
| n | % | val% | |
|---|---|---|---|
| Yes | 3257 | 91.6 | 99.7 |
| No | 10 | 0.3 | 0.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 290 | 8.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Yes | 303 | 94.4 | 100 |
| No | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 18 | 5.6 | NA |
| Total | 321 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| Yes | 195 | 92.9 | 100 |
| No | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| Yes | 289 | 91.7 | 99.3 |
| No | 2 | 0.6 | 0.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Yes | 343 | 96.3 | 99.4 |
| No | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Yes | 526 | 89.9 | 99.2 |
| No | 4 | 0.7 | 0.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 55 | 9.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Yes | 1586 | 90.4 | 99.9 |
| No | 2 | 0.1 | 0.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 166 | 9.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Yes | 15 | 93.8 | 100 |
| No | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100 |
A4. What is your month and year of birth?
# a4month
a4month <- as.factor(d[,"a4month"])
new.d <- data.frame(new.d, a4month)
new.d <- apply_labels(new.d, a4month = "Month of birth")
temp.d <- data.frame (new.d, a4month)
result<-questionr::freq(temp.d$a4month, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A4: Month of birth")
| n | % | val% | |
|---|---|---|---|
| 1 | 303 | 8.5 | 8.5 |
| 10 | 314 | 8.8 | 8.8 |
| 11 | 283 | 8.0 | 8.0 |
| 12 | 333 | 9.4 | 9.4 |
| 18 | 1 | 0.0 | 0.0 |
| 2 | 266 | 7.5 | 7.5 |
| 22 | 1 | 0.0 | 0.0 |
| 24 | 1 | 0.0 | 0.0 |
| 25 | 1 | 0.0 | 0.0 |
| 26 | 1 | 0.0 | 0.0 |
| 3 | 282 | 7.9 | 7.9 |
| 31 | 1 | 0.0 | 0.0 |
| 33 | 1 | 0.0 | 0.0 |
| 35 | 1 | 0.0 | 0.0 |
| 4 | 246 | 6.9 | 6.9 |
| 48 | 1 | 0.0 | 0.0 |
| 5 | 269 | 7.6 | 7.6 |
| 57 | 1 | 0.0 | 0.0 |
| 58 | 1 | 0.0 | 0.0 |
| 6 | 297 | 8.3 | 8.3 |
| 61 | 1 | 0.0 | 0.0 |
| 7 | 297 | 8.3 | 8.3 |
| 71 | 2 | 0.1 | 0.1 |
| 8 | 336 | 9.4 | 9.4 |
| 9 | 293 | 8.2 | 8.2 |
| 96 | 1 | 0.0 | 0.0 |
| “NA” | 23 | 0.6 | 0.6 |
| Total | 3557 | 100.0 | 100.0 |
#a4year
a4year <- as.factor(d[,"a4year"])
new.d <- data.frame(new.d, a4year)
new.d <- apply_labels(new.d, a4year = "Year of birth")
temp.d <- data.frame (new.d, a4year)
result<-questionr::freq(temp.d$a4year, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A4: Year of birth")
| n | % | val% | |
|---|---|---|---|
| 1062 | 1 | 0.0 | 0.0 |
| 1340 | 1 | 0.0 | 0.0 |
| 1930 | 1 | 0.0 | 0.0 |
| 1933 | 1 | 0.0 | 0.0 |
| 1936 | 1 | 0.0 | 0.0 |
| 1937 | 10 | 0.3 | 0.3 |
| 1938 | 10 | 0.3 | 0.3 |
| 1939 | 9 | 0.3 | 0.3 |
| 1940 | 19 | 0.5 | 0.5 |
| 1941 | 59 | 1.7 | 1.7 |
| 1942 | 63 | 1.8 | 1.8 |
| 1943 | 84 | 2.4 | 2.4 |
| 1944 | 85 | 2.4 | 2.4 |
| 1945 | 104 | 2.9 | 2.9 |
| 1946 | 145 | 4.1 | 4.1 |
| 1947 | 140 | 3.9 | 3.9 |
| 1948 | 192 | 5.4 | 5.4 |
| 1949 | 201 | 5.7 | 5.7 |
| 1950 | 208 | 5.8 | 5.8 |
| 1951 | 199 | 5.6 | 5.6 |
| 1952 | 187 | 5.3 | 5.3 |
| 1953 | 175 | 4.9 | 4.9 |
| 1954 | 180 | 5.1 | 5.1 |
| 1955 | 180 | 5.1 | 5.1 |
| 1956 | 191 | 5.4 | 5.4 |
| 1957 | 190 | 5.3 | 5.3 |
| 1958 | 133 | 3.7 | 3.7 |
| 1959 | 107 | 3.0 | 3.0 |
| 1960 | 147 | 4.1 | 4.1 |
| 1961 | 104 | 2.9 | 2.9 |
| 1962 | 79 | 2.2 | 2.2 |
| 1963 | 73 | 2.1 | 2.1 |
| 1964 | 57 | 1.6 | 1.6 |
| 1965 | 45 | 1.3 | 1.3 |
| 1966 | 37 | 1.0 | 1.0 |
| 1967 | 32 | 0.9 | 0.9 |
| 1968 | 24 | 0.7 | 0.7 |
| 1969 | 19 | 0.5 | 0.5 |
| 1970 | 13 | 0.4 | 0.4 |
| 1971 | 8 | 0.2 | 0.2 |
| 1972 | 3 | 0.1 | 0.1 |
| 1973 | 12 | 0.3 | 0.3 |
| 1974 | 1 | 0.0 | 0.0 |
| 1976 | 2 | 0.1 | 0.1 |
| 1977 | 1 | 0.0 | 0.0 |
| 1978 | 1 | 0.0 | 0.0 |
| 2015 | 3 | 0.1 | 0.1 |
| 2018 | 1 | 0.0 | 0.0 |
| 748 | 1 | 0.0 | 0.0 |
| “NA” | 18 | 0.5 | 0.5 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 28 | 8.7 | 8.7 |
| 10 | 27 | 8.4 | 8.4 |
| 11 | 28 | 8.7 | 8.7 |
| 12 | 29 | 9.0 | 9.0 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 23 | 7.2 | 7.2 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 31 | 9.7 | 9.7 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 19 | 5.9 | 5.9 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 22 | 6.9 | 6.9 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 6 | 29 | 9.0 | 9.0 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 23 | 7.2 | 7.2 |
| 71 | 0 | 0.0 | 0.0 |
| 8 | 35 | 10.9 | 10.9 |
| 9 | 23 | 7.2 | 7.2 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 2 | 0.6 | 0.6 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 2 | 0.6 | 0.6 |
| 1938 | 1 | 0.3 | 0.3 |
| 1939 | 3 | 0.9 | 0.9 |
| 1940 | 0 | 0.0 | 0.0 |
| 1941 | 2 | 0.6 | 0.6 |
| 1942 | 8 | 2.5 | 2.5 |
| 1943 | 8 | 2.5 | 2.5 |
| 1944 | 6 | 1.9 | 1.9 |
| 1945 | 8 | 2.5 | 2.5 |
| 1946 | 14 | 4.4 | 4.4 |
| 1947 | 15 | 4.7 | 4.7 |
| 1948 | 19 | 5.9 | 5.9 |
| 1949 | 15 | 4.7 | 4.7 |
| 1950 | 17 | 5.3 | 5.3 |
| 1951 | 16 | 5.0 | 5.0 |
| 1952 | 21 | 6.5 | 6.5 |
| 1953 | 16 | 5.0 | 5.0 |
| 1954 | 18 | 5.6 | 5.6 |
| 1955 | 18 | 5.6 | 5.6 |
| 1956 | 18 | 5.6 | 5.6 |
| 1957 | 16 | 5.0 | 5.0 |
| 1958 | 10 | 3.1 | 3.1 |
| 1959 | 8 | 2.5 | 2.5 |
| 1960 | 10 | 3.1 | 3.1 |
| 1961 | 13 | 4.0 | 4.0 |
| 1962 | 5 | 1.6 | 1.6 |
| 1963 | 5 | 1.6 | 1.6 |
| 1964 | 3 | 0.9 | 0.9 |
| 1965 | 4 | 1.2 | 1.2 |
| 1966 | 8 | 2.5 | 2.5 |
| 1967 | 5 | 1.6 | 1.6 |
| 1968 | 3 | 0.9 | 0.9 |
| 1969 | 2 | 0.6 | 0.6 |
| 1970 | 0 | 0.0 | 0.0 |
| 1971 | 0 | 0.0 | 0.0 |
| 1972 | 0 | 0.0 | 0.0 |
| 1973 | 1 | 0.3 | 0.3 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 0 | 0.0 | 0.0 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 1 | 0.3 | 0.3 |
| 2018 | 1 | 0.3 | 0.3 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 1 | 0.3 | 0.3 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 14 | 6.7 | 6.7 |
| 10 | 20 | 9.5 | 9.5 |
| 11 | 23 | 11.0 | 11.0 |
| 12 | 27 | 12.9 | 12.9 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 11 | 5.2 | 5.2 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 15 | 7.1 | 7.1 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 16 | 7.6 | 7.6 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 16 | 7.6 | 7.6 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 20 | 9.5 | 9.5 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 13 | 6.2 | 6.2 |
| 71 | 0 | 0.0 | 0.0 |
| 8 | 16 | 7.6 | 7.6 |
| 9 | 18 | 8.6 | 8.6 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 1 | 0.5 | 0.5 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 1 | 0.5 | 0.5 |
| 1938 | 1 | 0.5 | 0.5 |
| 1939 | 0 | 0.0 | 0.0 |
| 1940 | 1 | 0.5 | 0.5 |
| 1941 | 2 | 1.0 | 1.0 |
| 1942 | 8 | 3.8 | 3.8 |
| 1943 | 3 | 1.4 | 1.4 |
| 1944 | 3 | 1.4 | 1.4 |
| 1945 | 6 | 2.9 | 2.9 |
| 1946 | 11 | 5.2 | 5.2 |
| 1947 | 12 | 5.7 | 5.7 |
| 1948 | 8 | 3.8 | 3.8 |
| 1949 | 14 | 6.7 | 6.7 |
| 1950 | 13 | 6.2 | 6.2 |
| 1951 | 18 | 8.6 | 8.6 |
| 1952 | 10 | 4.8 | 4.8 |
| 1953 | 11 | 5.2 | 5.2 |
| 1954 | 13 | 6.2 | 6.2 |
| 1955 | 3 | 1.4 | 1.4 |
| 1956 | 5 | 2.4 | 2.4 |
| 1957 | 10 | 4.8 | 4.8 |
| 1958 | 16 | 7.6 | 7.6 |
| 1959 | 8 | 3.8 | 3.8 |
| 1960 | 9 | 4.3 | 4.3 |
| 1961 | 3 | 1.4 | 1.4 |
| 1962 | 1 | 0.5 | 0.5 |
| 1963 | 3 | 1.4 | 1.4 |
| 1964 | 3 | 1.4 | 1.4 |
| 1965 | 2 | 1.0 | 1.0 |
| 1966 | 2 | 1.0 | 1.0 |
| 1967 | 2 | 1.0 | 1.0 |
| 1968 | 1 | 0.5 | 0.5 |
| 1969 | 4 | 1.9 | 1.9 |
| 1970 | 1 | 0.5 | 0.5 |
| 1971 | 0 | 0.0 | 0.0 |
| 1972 | 0 | 0.0 | 0.0 |
| 1973 | 0 | 0.0 | 0.0 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 1 | 0.5 | 0.5 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 0 | 0.0 | 0.0 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 1 | 0.5 | 0.5 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 24 | 7.6 | 7.6 |
| 10 | 26 | 8.3 | 8.3 |
| 11 | 28 | 8.9 | 8.9 |
| 12 | 22 | 7.0 | 7.0 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 25 | 7.9 | 7.9 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 18 | 5.7 | 5.7 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 19 | 6.0 | 6.0 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 31 | 9.8 | 9.8 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 29 | 9.2 | 9.2 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 38 | 12.1 | 12.1 |
| 71 | 0 | 0.0 | 0.0 |
| 8 | 29 | 9.2 | 9.2 |
| 9 | 22 | 7.0 | 7.0 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 4 | 1.3 | 1.3 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1938 | 0 | 0.0 | 0.0 |
| 1939 | 0 | 0.0 | 0.0 |
| 1940 | 0 | 0.0 | 0.0 |
| 1941 | 6 | 1.9 | 1.9 |
| 1942 | 6 | 1.9 | 1.9 |
| 1943 | 6 | 1.9 | 1.9 |
| 1944 | 4 | 1.3 | 1.3 |
| 1945 | 13 | 4.1 | 4.1 |
| 1946 | 14 | 4.4 | 4.4 |
| 1947 | 11 | 3.5 | 3.5 |
| 1948 | 15 | 4.8 | 4.8 |
| 1949 | 24 | 7.6 | 7.6 |
| 1950 | 17 | 5.4 | 5.4 |
| 1951 | 17 | 5.4 | 5.4 |
| 1952 | 11 | 3.5 | 3.5 |
| 1953 | 15 | 4.8 | 4.8 |
| 1954 | 20 | 6.3 | 6.3 |
| 1955 | 17 | 5.4 | 5.4 |
| 1956 | 13 | 4.1 | 4.1 |
| 1957 | 14 | 4.4 | 4.4 |
| 1958 | 9 | 2.9 | 2.9 |
| 1959 | 9 | 2.9 | 2.9 |
| 1960 | 22 | 7.0 | 7.0 |
| 1961 | 11 | 3.5 | 3.5 |
| 1962 | 8 | 2.5 | 2.5 |
| 1963 | 10 | 3.2 | 3.2 |
| 1964 | 2 | 0.6 | 0.6 |
| 1965 | 8 | 2.5 | 2.5 |
| 1966 | 0 | 0.0 | 0.0 |
| 1967 | 2 | 0.6 | 0.6 |
| 1968 | 1 | 0.3 | 0.3 |
| 1969 | 2 | 0.6 | 0.6 |
| 1970 | 0 | 0.0 | 0.0 |
| 1971 | 1 | 0.3 | 0.3 |
| 1972 | 0 | 0.0 | 0.0 |
| 1973 | 1 | 0.3 | 0.3 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 0 | 0.0 | 0.0 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 1 | 0.3 | 0.3 |
| 2015 | 0 | 0.0 | 0.0 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 1 | 0.3 | 0.3 |
| “NA” | 4 | 1.3 | 1.3 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 28 | 7.9 | 7.9 |
| 10 | 36 | 10.1 | 10.1 |
| 11 | 24 | 6.7 | 6.7 |
| 12 | 23 | 6.5 | 6.5 |
| 18 | 1 | 0.3 | 0.3 |
| 2 | 28 | 7.9 | 7.9 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 24 | 6.7 | 6.7 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 31 | 8.7 | 8.7 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 21 | 5.9 | 5.9 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 34 | 9.6 | 9.6 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 29 | 8.1 | 8.1 |
| 71 | 1 | 0.3 | 0.3 |
| 8 | 40 | 11.2 | 11.2 |
| 9 | 36 | 10.1 | 10.1 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 1 | 0.3 | 0.3 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 4 | 1.1 | 1.1 |
| 1938 | 1 | 0.3 | 0.3 |
| 1939 | 3 | 0.8 | 0.8 |
| 1940 | 2 | 0.6 | 0.6 |
| 1941 | 8 | 2.2 | 2.2 |
| 1942 | 7 | 2.0 | 2.0 |
| 1943 | 9 | 2.5 | 2.5 |
| 1944 | 8 | 2.2 | 2.2 |
| 1945 | 9 | 2.5 | 2.5 |
| 1946 | 11 | 3.1 | 3.1 |
| 1947 | 18 | 5.1 | 5.1 |
| 1948 | 9 | 2.5 | 2.5 |
| 1949 | 14 | 3.9 | 3.9 |
| 1950 | 18 | 5.1 | 5.1 |
| 1951 | 16 | 4.5 | 4.5 |
| 1952 | 15 | 4.2 | 4.2 |
| 1953 | 11 | 3.1 | 3.1 |
| 1954 | 17 | 4.8 | 4.8 |
| 1955 | 26 | 7.3 | 7.3 |
| 1956 | 26 | 7.3 | 7.3 |
| 1957 | 27 | 7.6 | 7.6 |
| 1958 | 16 | 4.5 | 4.5 |
| 1959 | 8 | 2.2 | 2.2 |
| 1960 | 14 | 3.9 | 3.9 |
| 1961 | 12 | 3.4 | 3.4 |
| 1962 | 14 | 3.9 | 3.9 |
| 1963 | 8 | 2.2 | 2.2 |
| 1964 | 4 | 1.1 | 1.1 |
| 1965 | 3 | 0.8 | 0.8 |
| 1966 | 4 | 1.1 | 1.1 |
| 1967 | 3 | 0.8 | 0.8 |
| 1968 | 1 | 0.3 | 0.3 |
| 1969 | 3 | 0.8 | 0.8 |
| 1970 | 2 | 0.6 | 0.6 |
| 1971 | 1 | 0.3 | 0.3 |
| 1972 | 0 | 0.0 | 0.0 |
| 1973 | 2 | 0.6 | 0.6 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 0 | 0.0 | 0.0 |
| 1977 | 1 | 0.3 | 0.3 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 0 | 0.0 | 0.0 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 45 | 7.7 | 7.7 |
| 10 | 57 | 9.7 | 9.7 |
| 11 | 50 | 8.5 | 8.5 |
| 12 | 61 | 10.4 | 10.4 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 47 | 8.0 | 8.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.2 | 0.2 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 40 | 6.8 | 6.8 |
| 31 | 1 | 0.2 | 0.2 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 37 | 6.3 | 6.3 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 31 | 5.3 | 5.3 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 49 | 8.4 | 8.4 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 57 | 9.7 | 9.7 |
| 71 | 0 | 0.0 | 0.0 |
| 8 | 49 | 8.4 | 8.4 |
| 9 | 55 | 9.4 | 9.4 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 5 | 0.9 | 0.9 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 1 | 0.2 | 0.2 |
| 1937 | 3 | 0.5 | 0.5 |
| 1938 | 7 | 1.2 | 1.2 |
| 1939 | 2 | 0.3 | 0.3 |
| 1940 | 9 | 1.5 | 1.5 |
| 1941 | 12 | 2.1 | 2.1 |
| 1942 | 6 | 1.0 | 1.0 |
| 1943 | 13 | 2.2 | 2.2 |
| 1944 | 14 | 2.4 | 2.4 |
| 1945 | 21 | 3.6 | 3.6 |
| 1946 | 16 | 2.7 | 2.7 |
| 1947 | 23 | 3.9 | 3.9 |
| 1948 | 31 | 5.3 | 5.3 |
| 1949 | 33 | 5.6 | 5.6 |
| 1950 | 31 | 5.3 | 5.3 |
| 1951 | 31 | 5.3 | 5.3 |
| 1952 | 28 | 4.8 | 4.8 |
| 1953 | 45 | 7.7 | 7.7 |
| 1954 | 25 | 4.3 | 4.3 |
| 1955 | 29 | 5.0 | 5.0 |
| 1956 | 38 | 6.5 | 6.5 |
| 1957 | 30 | 5.1 | 5.1 |
| 1958 | 19 | 3.2 | 3.2 |
| 1959 | 17 | 2.9 | 2.9 |
| 1960 | 19 | 3.2 | 3.2 |
| 1961 | 20 | 3.4 | 3.4 |
| 1962 | 13 | 2.2 | 2.2 |
| 1963 | 14 | 2.4 | 2.4 |
| 1964 | 9 | 1.5 | 1.5 |
| 1965 | 5 | 0.9 | 0.9 |
| 1966 | 3 | 0.5 | 0.5 |
| 1967 | 7 | 1.2 | 1.2 |
| 1968 | 2 | 0.3 | 0.3 |
| 1969 | 1 | 0.2 | 0.2 |
| 1970 | 2 | 0.3 | 0.3 |
| 1971 | 1 | 0.2 | 0.2 |
| 1972 | 1 | 0.2 | 0.2 |
| 1973 | 0 | 0.0 | 0.0 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 0 | 0.0 | 0.0 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 1 | 0.2 | 0.2 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 3 | 0.5 | 0.5 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 163 | 9.3 | 9.3 |
| 10 | 146 | 8.3 | 8.3 |
| 11 | 130 | 7.4 | 7.4 |
| 12 | 169 | 9.6 | 9.6 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 130 | 7.4 | 7.4 |
| 22 | 1 | 0.1 | 0.1 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.1 | 0.1 |
| 3 | 154 | 8.8 | 8.8 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.1 | 0.1 |
| 35 | 1 | 0.1 | 0.1 |
| 4 | 121 | 6.9 | 6.9 |
| 48 | 1 | 0.1 | 0.1 |
| 5 | 147 | 8.4 | 8.4 |
| 57 | 1 | 0.1 | 0.1 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 135 | 7.7 | 7.7 |
| 61 | 1 | 0.1 | 0.1 |
| 7 | 135 | 7.7 | 7.7 |
| 71 | 1 | 0.1 | 0.1 |
| 8 | 166 | 9.5 | 9.5 |
| 9 | 138 | 7.9 | 7.9 |
| 96 | 1 | 0.1 | 0.1 |
| “NA” | 11 | 0.6 | 0.6 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 1 | 0.1 | 0.1 |
| 1340 | 1 | 0.1 | 0.1 |
| 1930 | 1 | 0.1 | 0.1 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1938 | 0 | 0.0 | 0.0 |
| 1939 | 1 | 0.1 | 0.1 |
| 1940 | 7 | 0.4 | 0.4 |
| 1941 | 29 | 1.7 | 1.7 |
| 1942 | 28 | 1.6 | 1.6 |
| 1943 | 45 | 2.6 | 2.6 |
| 1944 | 50 | 2.9 | 2.9 |
| 1945 | 46 | 2.6 | 2.6 |
| 1946 | 79 | 4.5 | 4.5 |
| 1947 | 61 | 3.5 | 3.5 |
| 1948 | 109 | 6.2 | 6.2 |
| 1949 | 99 | 5.6 | 5.6 |
| 1950 | 111 | 6.3 | 6.3 |
| 1951 | 101 | 5.8 | 5.8 |
| 1952 | 101 | 5.8 | 5.8 |
| 1953 | 76 | 4.3 | 4.3 |
| 1954 | 86 | 4.9 | 4.9 |
| 1955 | 86 | 4.9 | 4.9 |
| 1956 | 88 | 5.0 | 5.0 |
| 1957 | 93 | 5.3 | 5.3 |
| 1958 | 63 | 3.6 | 3.6 |
| 1959 | 56 | 3.2 | 3.2 |
| 1960 | 72 | 4.1 | 4.1 |
| 1961 | 45 | 2.6 | 2.6 |
| 1962 | 37 | 2.1 | 2.1 |
| 1963 | 33 | 1.9 | 1.9 |
| 1964 | 36 | 2.1 | 2.1 |
| 1965 | 23 | 1.3 | 1.3 |
| 1966 | 19 | 1.1 | 1.1 |
| 1967 | 13 | 0.7 | 0.7 |
| 1968 | 16 | 0.9 | 0.9 |
| 1969 | 7 | 0.4 | 0.4 |
| 1970 | 8 | 0.5 | 0.5 |
| 1971 | 5 | 0.3 | 0.3 |
| 1972 | 2 | 0.1 | 0.1 |
| 1973 | 8 | 0.5 | 0.5 |
| 1974 | 1 | 0.1 | 0.1 |
| 1976 | 1 | 0.1 | 0.1 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 1 | 0.1 | 0.1 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 9 | 0.5 | 0.5 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 6.2 | 6.2 |
| 10 | 2 | 12.5 | 12.5 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 2 | 12.5 | 12.5 |
| 18 | 0 | 0.0 | 0.0 |
| 2 | 2 | 12.5 | 12.5 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 4 | 3 | 18.8 | 18.8 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 1 | 6.2 | 6.2 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 6 | 1 | 6.2 | 6.2 |
| 61 | 0 | 0.0 | 0.0 |
| 7 | 2 | 12.5 | 12.5 |
| 71 | 0 | 0.0 | 0.0 |
| 8 | 1 | 6.2 | 6.2 |
| 9 | 1 | 6.2 | 6.2 |
| 96 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1062 | 0 | 0.0 | 0.0 |
| 1340 | 0 | 0.0 | 0.0 |
| 1930 | 0 | 0.0 | 0.0 |
| 1933 | 0 | 0.0 | 0.0 |
| 1936 | 0 | 0.0 | 0.0 |
| 1937 | 0 | 0.0 | 0.0 |
| 1938 | 0 | 0.0 | 0.0 |
| 1939 | 0 | 0.0 | 0.0 |
| 1940 | 0 | 0.0 | 0.0 |
| 1941 | 0 | 0.0 | 0.0 |
| 1942 | 0 | 0.0 | 0.0 |
| 1943 | 0 | 0.0 | 0.0 |
| 1944 | 0 | 0.0 | 0.0 |
| 1945 | 1 | 6.2 | 6.2 |
| 1946 | 0 | 0.0 | 0.0 |
| 1947 | 0 | 0.0 | 0.0 |
| 1948 | 1 | 6.2 | 6.2 |
| 1949 | 2 | 12.5 | 12.5 |
| 1950 | 1 | 6.2 | 6.2 |
| 1951 | 0 | 0.0 | 0.0 |
| 1952 | 1 | 6.2 | 6.2 |
| 1953 | 1 | 6.2 | 6.2 |
| 1954 | 1 | 6.2 | 6.2 |
| 1955 | 1 | 6.2 | 6.2 |
| 1956 | 3 | 18.8 | 18.8 |
| 1957 | 0 | 0.0 | 0.0 |
| 1958 | 0 | 0.0 | 0.0 |
| 1959 | 1 | 6.2 | 6.2 |
| 1960 | 1 | 6.2 | 6.2 |
| 1961 | 0 | 0.0 | 0.0 |
| 1962 | 1 | 6.2 | 6.2 |
| 1963 | 0 | 0.0 | 0.0 |
| 1964 | 0 | 0.0 | 0.0 |
| 1965 | 0 | 0.0 | 0.0 |
| 1966 | 1 | 6.2 | 6.2 |
| 1967 | 0 | 0.0 | 0.0 |
| 1968 | 0 | 0.0 | 0.0 |
| 1969 | 0 | 0.0 | 0.0 |
| 1970 | 0 | 0.0 | 0.0 |
| 1971 | 0 | 0.0 | 0.0 |
| 1972 | 0 | 0.0 | 0.0 |
| 1973 | 0 | 0.0 | 0.0 |
| 1974 | 0 | 0.0 | 0.0 |
| 1976 | 0 | 0.0 | 0.0 |
| 1977 | 0 | 0.0 | 0.0 |
| 1978 | 0 | 0.0 | 0.0 |
| 2015 | 0 | 0.0 | 0.0 |
| 2018 | 0 | 0.0 | 0.0 |
| 748 | 0 | 0.0 | 0.0 |
| “NA” | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
a5 <- as.factor(d[,"a5"])
levels(a5) <- list(US="1",
Africa="2",
Cuba_Caribbean= "3",
Other="4",
Scantron_Error="*")
a5 <- ordered(a5, c("US","Africa","Cuba_Caribbean","Other","Scantron_Error"))
new.d <- data.frame(new.d, a5)
new.d <- apply_labels(new.d, a5 = "Born place")
temp.d <- data.frame (new.d, a5)
result<-questionr::freq(temp.d$a5, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A5: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| US | 3310 | 93.1 | 93.3 |
| Africa | 101 | 2.8 | 2.8 |
| Cuba_Caribbean | 84 | 2.4 | 2.4 |
| Other | 40 | 1.1 | 1.1 |
| Scantron_Error | 11 | 0.3 | 0.3 |
| NA | 11 | 0.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
#a5: other
a5other <- as.factor(d[,"a5other"])
new.d <- data.frame(new.d, a5other)
new.d <- apply_labels(new.d, a5other = "Born place other")
temp.d <- data.frame (new.d, a5other)
result<-questionr::freq(temp.d$a5other, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A5 other: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 1 | 0.0 | 0.0 |
| Barbados | 1 | 0.0 | 0.0 |
| Beaumont Texas | 1 | 0.0 | 0.0 |
| Belize | 1 | 0.0 | 0.0 |
| Belize Central America | 1 | 0.0 | 0.0 |
| Belize, Central America | 2 | 0.1 | 0.1 |
| Buffalo NY | 1 | 0.0 | 0.0 |
| Central America (Panama) | 1 | 0.0 | 0.0 |
| Central America Belize | 1 | 0.0 | 0.0 |
| Chatroux, France | 1 | 0.0 | 0.0 |
| Chicago IL | 1 | 0.0 | 0.0 |
| England | 1 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 1 | 0.0 | 0.0 |
| Germany | 2 | 0.1 | 0.1 |
| Ghana | 2 | 0.1 | 0.1 |
| Guinea-CKY | 1 | 0.0 | 0.0 |
| Guyana | 4 | 0.1 | 0.1 |
| Guyana: South America | 1 | 0.0 | 0.0 |
| Haiti | 6 | 0.2 | 0.2 |
| Heidleburg Germany | 1 | 0.0 | 0.0 |
| Jackson, Miss. | 1 | 0.0 | 0.0 |
| Jamaica | 9 | 0.3 | 0.3 |
| JAMAICA | 1 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.0 | 0.0 |
| Jamaican | 1 | 0.0 | 0.0 |
| Japan | 1 | 0.0 | 0.0 |
| Kientra, Morocco | 1 | 0.0 | 0.0 |
| Kingston, Jamaica | 1 | 0.0 | 0.0 |
| Liberia | 1 | 0.0 | 0.0 |
| London England | 1 | 0.0 | 0.0 |
| Macon County | 1 | 0.0 | 0.0 |
| Mississippi | 1 | 0.0 | 0.0 |
| “NA” | 3485 | 98.0 | 98.0 |
| Nassau Bahamas | 2 | 0.1 | 0.1 |
| New Orleans, LA | 1 | 0.0 | 0.0 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 1 | 0.0 | 0.0 |
| Panama | 1 | 0.0 | 0.0 |
| Panama City of Panama | 1 | 0.0 | 0.0 |
| San Diego, CA | 1 | 0.0 | 0.0 |
| Sierre Leone | 1 | 0.0 | 0.0 |
| Southampton, Bermuda | 1 | 0.0 | 0.0 |
| Trinidad | 1 | 0.0 | 0.0 |
| Trinidad and Tobago | 1 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.0 | 0.0 |
| UK | 1 | 0.0 | 0.0 |
| United States Texas | 1 | 0.0 | 0.0 |
| Upson County, GA | 1 | 0.0 | 0.0 |
| Venezuela | 1 | 0.0 | 0.0 |
| Venezuelan | 1 | 0.0 | 0.0 |
| West Indies | 1 | 0.0 | 0.0 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 293 | 91.3 | 92.1 |
| Africa | 10 | 3.1 | 3.1 |
| Cuba_Caribbean | 9 | 2.8 | 2.8 |
| Other | 4 | 1.2 | 1.3 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Beaumont Texas | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Buffalo NY | 1 | 0.3 | 0.3 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Central America Belize | 0 | 0.0 | 0.0 |
| Chatroux, France | 0 | 0.0 | 0.0 |
| Chicago IL | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guinea-CKY | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 2 | 0.6 | 0.6 |
| Heidleburg Germany | 0 | 0.0 | 0.0 |
| Jackson, Miss. | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| Kientra, Morocco | 0 | 0.0 | 0.0 |
| Kingston, Jamaica | 0 | 0.0 | 0.0 |
| Liberia | 0 | 0.0 | 0.0 |
| London England | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 1 | 0.3 | 0.3 |
| “NA” | 311 | 96.9 | 96.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| New Orleans, LA | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Panama | 1 | 0.3 | 0.3 |
| Panama City of Panama | 1 | 0.3 | 0.3 |
| San Diego, CA | 0 | 0.0 | 0.0 |
| Sierre Leone | 1 | 0.3 | 0.3 |
| Southampton, Bermuda | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.3 | 0.3 |
| UK | 1 | 0.3 | 0.3 |
| United States Texas | 0 | 0.0 | 0.0 |
| Upson County, GA | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| Venezuelan | 0 | 0.0 | 0.0 |
| West Indies | 0 | 0.0 | 0.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 192 | 91.4 | 91.4 |
| Africa | 12 | 5.7 | 5.7 |
| Cuba_Caribbean | 3 | 1.4 | 1.4 |
| Other | 3 | 1.4 | 1.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 1 | 0.5 | 0.5 |
| Barbados | 0 | 0.0 | 0.0 |
| Beaumont Texas | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Central America Belize | 0 | 0.0 | 0.0 |
| Chatroux, France | 1 | 0.5 | 0.5 |
| Chicago IL | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guinea-CKY | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Heidleburg Germany | 0 | 0.0 | 0.0 |
| Jackson, Miss. | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| Kientra, Morocco | 0 | 0.0 | 0.0 |
| Kingston, Jamaica | 0 | 0.0 | 0.0 |
| Liberia | 0 | 0.0 | 0.0 |
| London England | 1 | 0.5 | 0.5 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| “NA” | 206 | 98.1 | 98.1 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| New Orleans, LA | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 1 | 0.5 | 0.5 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| San Diego, CA | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Southampton, Bermuda | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| UK | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Upson County, GA | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| Venezuelan | 0 | 0.0 | 0.0 |
| West Indies | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 275 | 87.3 | 87.9 |
| Africa | 23 | 7.3 | 7.3 |
| Cuba_Caribbean | 4 | 1.3 | 1.3 |
| Other | 8 | 2.5 | 2.6 |
| Scantron_Error | 3 | 1.0 | 1.0 |
| NA | 2 | 0.6 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Beaumont Texas | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Central America Belize | 0 | 0.0 | 0.0 |
| Chatroux, France | 0 | 0.0 | 0.0 |
| Chicago IL | 0 | 0.0 | 0.0 |
| England | 1 | 0.3 | 0.3 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 1 | 0.3 | 0.3 |
| Ghana | 1 | 0.3 | 0.3 |
| Guinea-CKY | 0 | 0.0 | 0.0 |
| Guyana | 1 | 0.3 | 0.3 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Heidleburg Germany | 0 | 0.0 | 0.0 |
| Jackson, Miss. | 1 | 0.3 | 0.3 |
| Jamaica | 1 | 0.3 | 0.3 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.3 | 0.3 |
| Jamaican | 1 | 0.3 | 0.3 |
| Japan | 0 | 0.0 | 0.0 |
| Kientra, Morocco | 1 | 0.3 | 0.3 |
| Kingston, Jamaica | 0 | 0.0 | 0.0 |
| Liberia | 0 | 0.0 | 0.0 |
| London England | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| “NA” | 301 | 95.6 | 95.6 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| New Orleans, LA | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| San Diego, CA | 1 | 0.3 | 0.3 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Southampton, Bermuda | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| UK | 0 | 0.0 | 0.0 |
| United States Texas | 1 | 0.3 | 0.3 |
| Upson County, GA | 0 | 0.0 | 0.0 |
| Venezuela | 1 | 0.3 | 0.3 |
| Venezuelan | 1 | 0.3 | 0.3 |
| West Indies | 0 | 0.0 | 0.0 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 353 | 99.2 | 99.4 |
| Africa | 1 | 0.3 | 0.3 |
| Cuba_Caribbean | 1 | 0.3 | 0.3 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.3 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0 | 0 |
| Barbados | 0 | 0 | 0 |
| Beaumont Texas | 0 | 0 | 0 |
| Belize | 0 | 0 | 0 |
| Belize Central America | 0 | 0 | 0 |
| Belize, Central America | 0 | 0 | 0 |
| Buffalo NY | 0 | 0 | 0 |
| Central America (Panama) | 0 | 0 | 0 |
| Central America Belize | 0 | 0 | 0 |
| Chatroux, France | 0 | 0 | 0 |
| Chicago IL | 0 | 0 | 0 |
| England | 0 | 0 | 0 |
| Ethiopia | 0 | 0 | 0 |
| Georgia Monroe Walton County | 0 | 0 | 0 |
| Germany | 0 | 0 | 0 |
| Ghana | 0 | 0 | 0 |
| Guinea-CKY | 0 | 0 | 0 |
| Guyana | 0 | 0 | 0 |
| Guyana: South America | 0 | 0 | 0 |
| Haiti | 0 | 0 | 0 |
| Heidleburg Germany | 0 | 0 | 0 |
| Jackson, Miss. | 0 | 0 | 0 |
| Jamaica | 0 | 0 | 0 |
| JAMAICA | 0 | 0 | 0 |
| Jamaica WI | 0 | 0 | 0 |
| Jamaican | 0 | 0 | 0 |
| Japan | 0 | 0 | 0 |
| Kientra, Morocco | 0 | 0 | 0 |
| Kingston, Jamaica | 0 | 0 | 0 |
| Liberia | 0 | 0 | 0 |
| London England | 0 | 0 | 0 |
| Macon County | 0 | 0 | 0 |
| Mississippi | 0 | 0 | 0 |
| “NA” | 356 | 100 | 100 |
| Nassau Bahamas | 0 | 0 | 0 |
| New Orleans, LA | 0 | 0 | 0 |
| Nigeria | 0 | 0 | 0 |
| Nigeria. | 0 | 0 | 0 |
| Panama | 0 | 0 | 0 |
| Panama City of Panama | 0 | 0 | 0 |
| San Diego, CA | 0 | 0 | 0 |
| Sierre Leone | 0 | 0 | 0 |
| Southampton, Bermuda | 0 | 0 | 0 |
| Trinidad | 0 | 0 | 0 |
| Trinidad and Tobago | 0 | 0 | 0 |
| Trinidad. | 0 | 0 | 0 |
| UK | 0 | 0 | 0 |
| United States Texas | 0 | 0 | 0 |
| Upson County, GA | 0 | 0 | 0 |
| Venezuela | 0 | 0 | 0 |
| Venezuelan | 0 | 0 | 0 |
| West Indies | 0 | 0 | 0 |
| Total | 356 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| US | 575 | 98.3 | 98.5 |
| Africa | 2 | 0.3 | 0.3 |
| Cuba_Caribbean | 6 | 1.0 | 1.0 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 1 | 0.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Beaumont Texas | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Central America Belize | 0 | 0.0 | 0.0 |
| Chatroux, France | 0 | 0.0 | 0.0 |
| Chicago IL | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guinea-CKY | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Heidleburg Germany | 0 | 0.0 | 0.0 |
| Jackson, Miss. | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| Kientra, Morocco | 0 | 0.0 | 0.0 |
| Kingston, Jamaica | 0 | 0.0 | 0.0 |
| Liberia | 0 | 0.0 | 0.0 |
| London England | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| “NA” | 584 | 99.8 | 99.8 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| New Orleans, LA | 1 | 0.2 | 0.2 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| San Diego, CA | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Southampton, Bermuda | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| UK | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Upson County, GA | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| Venezuelan | 0 | 0.0 | 0.0 |
| West Indies | 0 | 0.0 | 0.0 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 1607 | 91.6 | 91.8 |
| Africa | 53 | 3.0 | 3.0 |
| Cuba_Caribbean | 60 | 3.4 | 3.4 |
| Other | 25 | 1.4 | 1.4 |
| Scantron_Error | 5 | 0.3 | 0.3 |
| NA | 4 | 0.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 1 | 0.1 | 0.1 |
| Beaumont Texas | 1 | 0.1 | 0.1 |
| Belize | 1 | 0.1 | 0.1 |
| Belize Central America | 1 | 0.1 | 0.1 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Central America (Panama) | 1 | 0.1 | 0.1 |
| Central America Belize | 1 | 0.1 | 0.1 |
| Chatroux, France | 0 | 0.0 | 0.0 |
| Chicago IL | 1 | 0.1 | 0.1 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.1 | 0.1 |
| Georgia Monroe Walton County | 1 | 0.1 | 0.1 |
| Germany | 1 | 0.1 | 0.1 |
| Ghana | 1 | 0.1 | 0.1 |
| Guinea-CKY | 1 | 0.1 | 0.1 |
| Guyana | 3 | 0.2 | 0.2 |
| Guyana: South America | 1 | 0.1 | 0.1 |
| Haiti | 4 | 0.2 | 0.2 |
| Heidleburg Germany | 1 | 0.1 | 0.1 |
| Jackson, Miss. | 0 | 0.0 | 0.0 |
| Jamaica | 8 | 0.5 | 0.5 |
| JAMAICA | 1 | 0.1 | 0.1 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Japan | 1 | 0.1 | 0.1 |
| Kientra, Morocco | 0 | 0.0 | 0.0 |
| Kingston, Jamaica | 1 | 0.1 | 0.1 |
| Liberia | 1 | 0.1 | 0.1 |
| London England | 0 | 0.0 | 0.0 |
| Macon County | 1 | 0.1 | 0.1 |
| Mississippi | 0 | 0.0 | 0.0 |
| “NA” | 1711 | 97.5 | 97.5 |
| Nassau Bahamas | 2 | 0.1 | 0.1 |
| New Orleans, LA | 0 | 0.0 | 0.0 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| San Diego, CA | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Southampton, Bermuda | 1 | 0.1 | 0.1 |
| Trinidad | 1 | 0.1 | 0.1 |
| Trinidad and Tobago | 1 | 0.1 | 0.1 |
| Trinidad. | 0 | 0.0 | 0.0 |
| UK | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Upson County, GA | 1 | 0.1 | 0.1 |
| Venezuela | 0 | 0.0 | 0.0 |
| Venezuelan | 0 | 0.0 | 0.0 |
| West Indies | 1 | 0.1 | 0.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 15 | 93.8 | 93.8 |
| Africa | 0 | 0.0 | 0.0 |
| Cuba_Caribbean | 1 | 6.2 | 6.2 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0 | 0 |
| Barbados | 0 | 0 | 0 |
| Beaumont Texas | 0 | 0 | 0 |
| Belize | 0 | 0 | 0 |
| Belize Central America | 0 | 0 | 0 |
| Belize, Central America | 0 | 0 | 0 |
| Buffalo NY | 0 | 0 | 0 |
| Central America (Panama) | 0 | 0 | 0 |
| Central America Belize | 0 | 0 | 0 |
| Chatroux, France | 0 | 0 | 0 |
| Chicago IL | 0 | 0 | 0 |
| England | 0 | 0 | 0 |
| Ethiopia | 0 | 0 | 0 |
| Georgia Monroe Walton County | 0 | 0 | 0 |
| Germany | 0 | 0 | 0 |
| Ghana | 0 | 0 | 0 |
| Guinea-CKY | 0 | 0 | 0 |
| Guyana | 0 | 0 | 0 |
| Guyana: South America | 0 | 0 | 0 |
| Haiti | 0 | 0 | 0 |
| Heidleburg Germany | 0 | 0 | 0 |
| Jackson, Miss. | 0 | 0 | 0 |
| Jamaica | 0 | 0 | 0 |
| JAMAICA | 0 | 0 | 0 |
| Jamaica WI | 0 | 0 | 0 |
| Jamaican | 0 | 0 | 0 |
| Japan | 0 | 0 | 0 |
| Kientra, Morocco | 0 | 0 | 0 |
| Kingston, Jamaica | 0 | 0 | 0 |
| Liberia | 0 | 0 | 0 |
| London England | 0 | 0 | 0 |
| Macon County | 0 | 0 | 0 |
| Mississippi | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Nassau Bahamas | 0 | 0 | 0 |
| New Orleans, LA | 0 | 0 | 0 |
| Nigeria | 0 | 0 | 0 |
| Nigeria. | 0 | 0 | 0 |
| Panama | 0 | 0 | 0 |
| Panama City of Panama | 0 | 0 | 0 |
| San Diego, CA | 0 | 0 | 0 |
| Sierre Leone | 0 | 0 | 0 |
| Southampton, Bermuda | 0 | 0 | 0 |
| Trinidad | 0 | 0 | 0 |
| Trinidad and Tobago | 0 | 0 | 0 |
| Trinidad. | 0 | 0 | 0 |
| UK | 0 | 0 | 0 |
| United States Texas | 0 | 0 | 0 |
| Upson County, GA | 0 | 0 | 0 |
| Venezuela | 0 | 0 | 0 |
| Venezuelan | 0 | 0 | 0 |
| West Indies | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
a6 <- as.factor(d[,"a6"])
levels(a6) <- list(US="1",
Africa="2",
Cuba_Caribbean= "3",
Other="4",
Scantron_Error="*")
a6 <- ordered(a6, c("US","Africa","Cuba_Caribbean","Other","Scantron_Error"))
new.d <- data.frame(new.d, a6)
new.d <- apply_labels(new.d, a6 = "Born place")
temp.d <- data.frame (new.d, a6)
result<-questionr::freq(temp.d$a6, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a6: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| US | 3271 | 92.0 | 92.8 |
| Africa | 101 | 2.8 | 2.9 |
| Cuba_Caribbean | 95 | 2.7 | 2.7 |
| Other | 51 | 1.4 | 1.4 |
| Scantron_Error | 6 | 0.2 | 0.2 |
| NA | 33 | 0.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
#a6: other
a6other <- as.factor(d[,"a6other"])
new.d <- data.frame(new.d, a6other)
new.d <- apply_labels(new.d, a6other = "Born place other")
temp.d <- data.frame (new.d, a6other)
result<-questionr::freq(temp.d$a6other, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a6 other: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| Barbados | 1 | 0.0 | 0.0 |
| Belize | 1 | 0.0 | 0.0 |
| Belize Central America | 1 | 0.0 | 0.0 |
| Belize, Central America | 2 | 0.1 | 0.1 |
| Biological father unknown | 1 | 0.0 | 0.0 |
| Blackstone, VA | 1 | 0.0 | 0.0 |
| Bombay. | 1 | 0.0 | 0.0 |
| British Honduras. | 1 | 0.0 | 0.0 |
| Canada | 1 | 0.0 | 0.0 |
| Canada. | 1 | 0.0 | 0.0 |
| Central America (Panama) | 1 | 0.0 | 0.0 |
| Cleveland Mississippi | 1 | 0.0 | 0.0 |
| Dead | 1 | 0.0 | 0.0 |
| Don’t know | 2 | 0.1 | 0.1 |
| East Pakistan | 1 | 0.0 | 0.0 |
| England | 1 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 1 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 1 | 0.0 | 0.0 |
| Germany | 1 | 0.0 | 0.0 |
| Ghana | 1 | 0.0 | 0.0 |
| Guyana | 4 | 0.1 | 0.1 |
| Guyana: South America | 1 | 0.0 | 0.0 |
| Haiti | 6 | 0.2 | 0.2 |
| Honduras, Central America | 1 | 0.0 | 0.0 |
| I don’t know | 1 | 0.0 | 0.0 |
| I was adopted, no info | 1 | 0.0 | 0.0 |
| Jamaica | 11 | 0.3 | 0.3 |
| JAMAICA | 1 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.0 | 0.0 |
| Jamaican | 1 | 0.0 | 0.0 |
| Macon County | 1 | 0.0 | 0.0 |
| Mississippi | 2 | 0.1 | 0.1 |
| Montserrat British VI | 1 | 0.0 | 0.0 |
| “NA” | 3478 | 97.8 | 97.8 |
| Nassau Bahamas | 2 | 0.1 | 0.1 |
| Never knew my father | 1 | 0.0 | 0.0 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 1 | 0.0 | 0.0 |
| Not known | 1 | 0.0 | 0.0 |
| Panama | 2 | 0.1 | 0.1 |
| Panama-Central America | 1 | 0.0 | 0.0 |
| Panama Canal Zone | 1 | 0.0 | 0.0 |
| Panama City of Panama | 1 | 0.0 | 0.0 |
| Sierre Leone | 1 | 0.0 | 0.0 |
| Trinidad | 1 | 0.0 | 0.0 |
| Trinidad and Tobago | 1 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.0 | 0.0 |
| United S Texas | 1 | 0.0 | 0.0 |
| Unknown | 4 | 0.1 | 0.1 |
| Venezuela | 1 | 0.0 | 0.0 |
| west Indies | 1 | 0.0 | 0.0 |
| Yatesville GA | 1 | 0.0 | 0.0 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 293 | 91.3 | 91.6 |
| Africa | 10 | 3.1 | 3.1 |
| Cuba_Caribbean | 10 | 3.1 | 3.1 |
| Other | 5 | 1.6 | 1.6 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 1 | 0.3 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Biological father unknown | 0 | 0.0 | 0.0 |
| Blackstone, VA | 0 | 0.0 | 0.0 |
| Bombay. | 0 | 0.0 | 0.0 |
| British Honduras. | 0 | 0.0 | 0.0 |
| Canada | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Cleveland Mississippi | 1 | 0.3 | 0.3 |
| Dead | 0 | 0.0 | 0.0 |
| Don’t know | 0 | 0.0 | 0.0 |
| East Pakistan | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 2 | 0.6 | 0.6 |
| Honduras, Central America | 0 | 0.0 | 0.0 |
| I don’t know | 0 | 0.0 | 0.0 |
| I was adopted, no info | 0 | 0.0 | 0.0 |
| Jamaica | 2 | 0.6 | 0.6 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 311 | 96.9 | 96.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Never knew my father | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Not known | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama-Central America | 0 | 0.0 | 0.0 |
| Panama Canal Zone | 0 | 0.0 | 0.0 |
| Panama City of Panama | 1 | 0.3 | 0.3 |
| Sierre Leone | 1 | 0.3 | 0.3 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.3 | 0.3 |
| United S Texas | 0 | 0.0 | 0.0 |
| Unknown | 1 | 0.3 | 0.3 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Yatesville GA | 0 | 0.0 | 0.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 189 | 90.0 | 91.3 |
| Africa | 12 | 5.7 | 5.8 |
| Cuba_Caribbean | 4 | 1.9 | 1.9 |
| Other | 2 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 1.4 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Biological father unknown | 0 | 0.0 | 0.0 |
| Blackstone, VA | 0 | 0.0 | 0.0 |
| Bombay. | 1 | 0.5 | 0.5 |
| British Honduras. | 0 | 0.0 | 0.0 |
| Canada | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Cleveland Mississippi | 0 | 0.0 | 0.0 |
| Dead | 0 | 0.0 | 0.0 |
| Don’t know | 0 | 0.0 | 0.0 |
| East Pakistan | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Honduras, Central America | 0 | 0.0 | 0.0 |
| I don’t know | 0 | 0.0 | 0.0 |
| I was adopted, no info | 0 | 0.0 | 0.0 |
| Jamaica | 1 | 0.5 | 0.5 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 205 | 97.6 | 97.6 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Never knew my father | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 1 | 0.5 | 0.5 |
| Not known | 0 | 0.0 | 0.0 |
| Panama | 1 | 0.5 | 0.5 |
| Panama-Central America | 0 | 0.0 | 0.0 |
| Panama Canal Zone | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United S Texas | 0 | 0.0 | 0.0 |
| Unknown | 1 | 0.5 | 0.5 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Yatesville GA | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 270 | 85.7 | 87.1 |
| Africa | 23 | 7.3 | 7.4 |
| Cuba_Caribbean | 7 | 2.2 | 2.3 |
| Other | 9 | 2.9 | 2.9 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 5 | 1.6 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Biological father unknown | 0 | 0.0 | 0.0 |
| Blackstone, VA | 1 | 0.3 | 0.3 |
| Bombay. | 0 | 0.0 | 0.0 |
| British Honduras. | 0 | 0.0 | 0.0 |
| Canada | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Cleveland Mississippi | 0 | 0.0 | 0.0 |
| Dead | 0 | 0.0 | 0.0 |
| Don’t know | 1 | 0.3 | 0.3 |
| East Pakistan | 0 | 0.0 | 0.0 |
| England | 1 | 0.3 | 0.3 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 1 | 0.3 | 0.3 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Honduras, Central America | 0 | 0.0 | 0.0 |
| I don’t know | 0 | 0.0 | 0.0 |
| I was adopted, no info | 0 | 0.0 | 0.0 |
| Jamaica | 1 | 0.3 | 0.3 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.3 | 0.3 |
| Jamaican | 1 | 0.3 | 0.3 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 1 | 0.3 | 0.3 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 302 | 95.9 | 95.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Never knew my father | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Not known | 1 | 0.3 | 0.3 |
| Panama | 1 | 0.3 | 0.3 |
| Panama-Central America | 0 | 0.0 | 0.0 |
| Panama Canal Zone | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United S Texas | 1 | 0.3 | 0.3 |
| Unknown | 0 | 0.0 | 0.0 |
| Venezuela | 1 | 0.3 | 0.3 |
| west Indies | 0 | 0.0 | 0.0 |
| Yatesville GA | 0 | 0.0 | 0.0 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 345 | 96.9 | 98.3 |
| Africa | 1 | 0.3 | 0.3 |
| Cuba_Caribbean | 2 | 0.6 | 0.6 |
| Other | 3 | 0.8 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.4 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Biological father unknown | 0 | 0.0 | 0.0 |
| Blackstone, VA | 0 | 0.0 | 0.0 |
| Bombay. | 0 | 0.0 | 0.0 |
| British Honduras. | 0 | 0.0 | 0.0 |
| Canada | 1 | 0.3 | 0.3 |
| Canada. | 1 | 0.3 | 0.3 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Cleveland Mississippi | 0 | 0.0 | 0.0 |
| Dead | 0 | 0.0 | 0.0 |
| Don’t know | 0 | 0.0 | 0.0 |
| East Pakistan | 1 | 0.3 | 0.3 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Honduras, Central America | 0 | 0.0 | 0.0 |
| I don’t know | 0 | 0.0 | 0.0 |
| I was adopted, no info | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 352 | 98.9 | 98.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Never knew my father | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Not known | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama-Central America | 0 | 0.0 | 0.0 |
| Panama Canal Zone | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United S Texas | 0 | 0.0 | 0.0 |
| Unknown | 1 | 0.3 | 0.3 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Yatesville GA | 0 | 0.0 | 0.0 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 574 | 98.1 | 98.5 |
| Africa | 2 | 0.3 | 0.3 |
| Cuba_Caribbean | 5 | 0.9 | 0.9 |
| Other | 2 | 0.3 | 0.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Biological father unknown | 0 | 0.0 | 0.0 |
| Blackstone, VA | 0 | 0.0 | 0.0 |
| Bombay. | 0 | 0.0 | 0.0 |
| British Honduras. | 1 | 0.2 | 0.2 |
| Canada | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Panama) | 0 | 0.0 | 0.0 |
| Cleveland Mississippi | 0 | 0.0 | 0.0 |
| Dead | 0 | 0.0 | 0.0 |
| Don’t know | 0 | 0.0 | 0.0 |
| East Pakistan | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Father’s birthplace is unknown. | 0 | 0.0 | 0.0 |
| Georgia Monroe Walton County | 0 | 0.0 | 0.0 |
| Germany | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Honduras, Central America | 0 | 0.0 | 0.0 |
| I don’t know | 0 | 0.0 | 0.0 |
| I was adopted, no info | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 583 | 99.7 | 99.7 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Never knew my father | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Not known | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama-Central America | 0 | 0.0 | 0.0 |
| Panama Canal Zone | 1 | 0.2 | 0.2 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United S Texas | 0 | 0.0 | 0.0 |
| Unknown | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Yatesville GA | 0 | 0.0 | 0.0 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 1585 | 90.4 | 91.2 |
| Africa | 53 | 3.0 | 3.1 |
| Cuba_Caribbean | 66 | 3.8 | 3.8 |
| Other | 30 | 1.7 | 1.7 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 17 | 1.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 1 | 0.1 | 0.1 |
| Belize | 1 | 0.1 | 0.1 |
| Belize Central America | 1 | 0.1 | 0.1 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Biological father unknown | 1 | 0.1 | 0.1 |
| Blackstone, VA | 0 | 0.0 | 0.0 |
| Bombay. | 0 | 0.0 | 0.0 |
| British Honduras. | 0 | 0.0 | 0.0 |
| Canada | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Panama) | 1 | 0.1 | 0.1 |
| Cleveland Mississippi | 0 | 0.0 | 0.0 |
| Dead | 1 | 0.1 | 0.1 |
| Don’t know | 1 | 0.1 | 0.1 |
| East Pakistan | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.1 | 0.1 |
| Father’s birthplace is unknown. | 1 | 0.1 | 0.1 |
| Georgia Monroe Walton County | 1 | 0.1 | 0.1 |
| Germany | 1 | 0.1 | 0.1 |
| Ghana | 1 | 0.1 | 0.1 |
| Guyana | 3 | 0.2 | 0.2 |
| Guyana: South America | 1 | 0.1 | 0.1 |
| Haiti | 4 | 0.2 | 0.2 |
| Honduras, Central America | 1 | 0.1 | 0.1 |
| I don’t know | 1 | 0.1 | 0.1 |
| I was adopted, no info | 1 | 0.1 | 0.1 |
| Jamaica | 7 | 0.4 | 0.4 |
| JAMAICA | 1 | 0.1 | 0.1 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Jamaican | 0 | 0.0 | 0.0 |
| Macon County | 1 | 0.1 | 0.1 |
| Mississippi | 1 | 0.1 | 0.1 |
| Montserrat British VI | 1 | 0.1 | 0.1 |
| “NA” | 1709 | 97.4 | 97.4 |
| Nassau Bahamas | 2 | 0.1 | 0.1 |
| Never knew my father | 1 | 0.1 | 0.1 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 0 | 0.0 | 0.0 |
| Not known | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama-Central America | 1 | 0.1 | 0.1 |
| Panama Canal Zone | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 1 | 0.1 | 0.1 |
| Trinidad and Tobago | 1 | 0.1 | 0.1 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United S Texas | 0 | 0.0 | 0.0 |
| Unknown | 1 | 0.1 | 0.1 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 1 | 0.1 | 0.1 |
| Yatesville GA | 1 | 0.1 | 0.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 15 | 93.8 | 93.8 |
| Africa | 0 | 0.0 | 0.0 |
| Cuba_Caribbean | 1 | 6.2 | 6.2 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Barbados | 0 | 0 | 0 |
| Belize | 0 | 0 | 0 |
| Belize Central America | 0 | 0 | 0 |
| Belize, Central America | 0 | 0 | 0 |
| Biological father unknown | 0 | 0 | 0 |
| Blackstone, VA | 0 | 0 | 0 |
| Bombay. | 0 | 0 | 0 |
| British Honduras. | 0 | 0 | 0 |
| Canada | 0 | 0 | 0 |
| Canada. | 0 | 0 | 0 |
| Central America (Panama) | 0 | 0 | 0 |
| Cleveland Mississippi | 0 | 0 | 0 |
| Dead | 0 | 0 | 0 |
| Don’t know | 0 | 0 | 0 |
| East Pakistan | 0 | 0 | 0 |
| England | 0 | 0 | 0 |
| Ethiopia | 0 | 0 | 0 |
| Father’s birthplace is unknown. | 0 | 0 | 0 |
| Georgia Monroe Walton County | 0 | 0 | 0 |
| Germany | 0 | 0 | 0 |
| Ghana | 0 | 0 | 0 |
| Guyana | 0 | 0 | 0 |
| Guyana: South America | 0 | 0 | 0 |
| Haiti | 0 | 0 | 0 |
| Honduras, Central America | 0 | 0 | 0 |
| I don’t know | 0 | 0 | 0 |
| I was adopted, no info | 0 | 0 | 0 |
| Jamaica | 0 | 0 | 0 |
| JAMAICA | 0 | 0 | 0 |
| Jamaica WI | 0 | 0 | 0 |
| Jamaican | 0 | 0 | 0 |
| Macon County | 0 | 0 | 0 |
| Mississippi | 0 | 0 | 0 |
| Montserrat British VI | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Nassau Bahamas | 0 | 0 | 0 |
| Never knew my father | 0 | 0 | 0 |
| Nigeria | 0 | 0 | 0 |
| Nigeria. | 0 | 0 | 0 |
| Not known | 0 | 0 | 0 |
| Panama | 0 | 0 | 0 |
| Panama-Central America | 0 | 0 | 0 |
| Panama Canal Zone | 0 | 0 | 0 |
| Panama City of Panama | 0 | 0 | 0 |
| Sierre Leone | 0 | 0 | 0 |
| Trinidad | 0 | 0 | 0 |
| Trinidad and Tobago | 0 | 0 | 0 |
| Trinidad. | 0 | 0 | 0 |
| United S Texas | 0 | 0 | 0 |
| Unknown | 0 | 0 | 0 |
| Venezuela | 0 | 0 | 0 |
| west Indies | 0 | 0 | 0 |
| Yatesville GA | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
a7 <- as.factor(d[,"a7"])
levels(a7) <- list(US="1",
Africa="2",
Cuba_Caribbean= "3",
Other="4",
Scantron_Error="*")
a7 <- ordered(a7, c("US","Africa","Cuba_Caribbean","Other","Scantron_Error"))
new.d <- data.frame(new.d, a7)
new.d <- apply_labels(new.d, a7 = "Born place")
temp.d <- data.frame (new.d, a7)
result<-questionr::freq(temp.d$a7, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a7: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| US | 3296 | 92.7 | 93.2 |
| Africa | 98 | 2.8 | 2.8 |
| Cuba_Caribbean | 96 | 2.7 | 2.7 |
| Other | 42 | 1.2 | 1.2 |
| Scantron_Error | 5 | 0.1 | 0.1 |
| NA | 20 | 0.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
#a7: other
a7other <- as.factor(d[,"a7other"])
new.d <- data.frame(new.d, a7other)
new.d <- apply_labels(new.d, a7other = "Born place other")
temp.d <- data.frame (new.d, a7other)
result<-questionr::freq(temp.d$a7other, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a7 other: Where were you born?")
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 1 | 0.0 | 0.0 |
| Barbados | 1 | 0.0 | 0.0 |
| Belize | 1 | 0.0 | 0.0 |
| Belize Central America | 1 | 0.0 | 0.0 |
| Belize, Central America | 2 | 0.1 | 0.1 |
| Bremont, TX | 1 | 0.0 | 0.0 |
| Buffalo NY | 1 | 0.0 | 0.0 |
| Canada. | 1 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 1 | 0.0 | 0.0 |
| England | 1 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 1 | 0.0 | 0.0 |
| Ghana | 1 | 0.0 | 0.0 |
| Guyana | 4 | 0.1 | 0.1 |
| Guyana: South America | 1 | 0.0 | 0.0 |
| Haiti | 6 | 0.2 | 0.2 |
| Jamaica | 9 | 0.3 | 0.3 |
| JAMAICA | 1 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 1 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.0 | 0.0 |
| Japan | 3 | 0.1 | 0.1 |
| LA | 1 | 0.0 | 0.0 |
| Lamar County, GA | 1 | 0.0 | 0.0 |
| Macon County | 1 | 0.0 | 0.0 |
| Mexico | 1 | 0.0 | 0.0 |
| Mississippi | 2 | 0.1 | 0.1 |
| Montserrat British VI | 1 | 0.0 | 0.0 |
| “NA” | 3490 | 98.1 | 98.1 |
| Nassau Bahamas | 1 | 0.0 | 0.0 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 1 | 0.0 | 0.0 |
| No biological info, I was adopted. | 1 | 0.0 | 0.0 |
| Oklahoma | 1 | 0.0 | 0.0 |
| Panama | 3 | 0.1 | 0.1 |
| Panama City of Panama | 1 | 0.0 | 0.0 |
| Puerto Rican | 1 | 0.0 | 0.0 |
| Sierre Leone | 1 | 0.0 | 0.0 |
| Trinidad | 1 | 0.0 | 0.0 |
| Trinidad and Tobago | 1 | 0.0 | 0.0 |
| Trinidad West Indies | 1 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.0 | 0.0 |
| United States Texas | 1 | 0.0 | 0.0 |
| Venezuela | 2 | 0.1 | 0.1 |
| west Indies | 1 | 0.0 | 0.0 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 291 | 90.7 | 91.2 |
| Africa | 10 | 3.1 | 3.1 |
| Cuba_Caribbean | 11 | 3.4 | 3.4 |
| Other | 5 | 1.6 | 1.6 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Bremont, TX | 0 | 0.0 | 0.0 |
| Buffalo NY | 1 | 0.3 | 0.3 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 2 | 0.6 | 0.6 |
| Jamaica | 1 | 0.3 | 0.3 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| LA | 0 | 0.0 | 0.0 |
| Lamar County, GA | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mexico | 1 | 0.3 | 0.3 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 311 | 96.9 | 96.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| No biological info, I was adopted. | 0 | 0.0 | 0.0 |
| Oklahoma | 0 | 0.0 | 0.0 |
| Panama | 1 | 0.3 | 0.3 |
| Panama City of Panama | 1 | 0.3 | 0.3 |
| Puerto Rican | 0 | 0.0 | 0.0 |
| Sierre Leone | 1 | 0.3 | 0.3 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad West Indies | 0 | 0.0 | 0.0 |
| Trinidad. | 1 | 0.3 | 0.3 |
| United States Texas | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 192 | 91.4 | 91.4 |
| Africa | 12 | 5.7 | 5.7 |
| Cuba_Caribbean | 4 | 1.9 | 1.9 |
| Other | 2 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 1 | 0.5 | 0.5 |
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Bremont, TX | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Jamaica | 1 | 0.5 | 0.5 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| LA | 0 | 0.0 | 0.0 |
| Lamar County, GA | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mexico | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 207 | 98.6 | 98.6 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 1 | 0.5 | 0.5 |
| No biological info, I was adopted. | 0 | 0.0 | 0.0 |
| Oklahoma | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Puerto Rican | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad West Indies | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 269 | 85.4 | 87.6 |
| Africa | 22 | 7.0 | 7.2 |
| Cuba_Caribbean | 6 | 1.9 | 2.0 |
| Other | 9 | 2.9 | 2.9 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 8 | 2.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 1 | 0.3 | 0.3 |
| Bremont, TX | 1 | 0.3 | 0.3 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 0 | 0.0 | 0.0 |
| England | 1 | 0.3 | 0.3 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 1 | 0.3 | 0.3 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 0 | 0.0 | 0.0 |
| Jamaica WI | 1 | 0.3 | 0.3 |
| Japan | 1 | 0.3 | 0.3 |
| LA | 0 | 0.0 | 0.0 |
| Lamar County, GA | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mexico | 0 | 0.0 | 0.0 |
| Mississippi | 1 | 0.3 | 0.3 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 302 | 95.9 | 95.9 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| No biological info, I was adopted. | 0 | 0.0 | 0.0 |
| Oklahoma | 1 | 0.3 | 0.3 |
| Panama | 1 | 0.3 | 0.3 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Puerto Rican | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad West Indies | 1 | 0.3 | 0.3 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United States Texas | 1 | 0.3 | 0.3 |
| Venezuela | 2 | 0.6 | 0.6 |
| west Indies | 0 | 0.0 | 0.0 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 349 | 98.0 | 98.6 |
| Africa | 1 | 0.3 | 0.3 |
| Cuba_Caribbean | 2 | 0.6 | 0.6 |
| Other | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Bremont, TX | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Canada. | 1 | 0.3 | 0.3 |
| Central America (Colon, Panama) | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Japan | 1 | 0.3 | 0.3 |
| LA | 0 | 0.0 | 0.0 |
| Lamar County, GA | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mexico | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 354 | 99.4 | 99.4 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| No biological info, I was adopted. | 0 | 0.0 | 0.0 |
| Oklahoma | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Puerto Rican | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad West Indies | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 576 | 98.5 | 98.8 |
| Africa | 1 | 0.2 | 0.2 |
| Cuba_Caribbean | 6 | 1.0 | 1.0 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 0 | 0.0 | 0.0 |
| Belize | 0 | 0.0 | 0.0 |
| Belize Central America | 0 | 0.0 | 0.0 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Bremont, TX | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 0 | 0.0 | 0.0 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 0 | 0.0 | 0.0 |
| Georgia Good Hope Walton County | 0 | 0.0 | 0.0 |
| Ghana | 0 | 0.0 | 0.0 |
| Guyana | 0 | 0.0 | 0.0 |
| Guyana: South America | 0 | 0.0 | 0.0 |
| Haiti | 0 | 0.0 | 0.0 |
| Jamaica | 0 | 0.0 | 0.0 |
| JAMAICA | 0 | 0.0 | 0.0 |
| Jamaica BWI Kingston | 0 | 0.0 | 0.0 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Japan | 0 | 0.0 | 0.0 |
| LA | 1 | 0.2 | 0.2 |
| Lamar County, GA | 0 | 0.0 | 0.0 |
| Macon County | 0 | 0.0 | 0.0 |
| Mexico | 0 | 0.0 | 0.0 |
| Mississippi | 0 | 0.0 | 0.0 |
| Montserrat British VI | 0 | 0.0 | 0.0 |
| “NA” | 584 | 99.8 | 99.8 |
| Nassau Bahamas | 0 | 0.0 | 0.0 |
| Nigeria | 0 | 0.0 | 0.0 |
| Nigeria. | 0 | 0.0 | 0.0 |
| No biological info, I was adopted. | 0 | 0.0 | 0.0 |
| Oklahoma | 0 | 0.0 | 0.0 |
| Panama | 0 | 0.0 | 0.0 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Puerto Rican | 0 | 0.0 | 0.0 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 0 | 0.0 | 0.0 |
| Trinidad and Tobago | 0 | 0.0 | 0.0 |
| Trinidad West Indies | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 0 | 0.0 | 0.0 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 1604 | 91.4 | 91.8 |
| Africa | 52 | 3.0 | 3.0 |
| Cuba_Caribbean | 66 | 3.8 | 3.8 |
| Other | 24 | 1.4 | 1.4 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 6 | 0.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0.0 | 0.0 |
| Barbados | 1 | 0.1 | 0.1 |
| Belize | 1 | 0.1 | 0.1 |
| Belize Central America | 1 | 0.1 | 0.1 |
| Belize, Central America | 0 | 0.0 | 0.0 |
| Bremont, TX | 0 | 0.0 | 0.0 |
| Buffalo NY | 0 | 0.0 | 0.0 |
| Canada. | 0 | 0.0 | 0.0 |
| Central America (Colon, Panama) | 1 | 0.1 | 0.1 |
| England | 0 | 0.0 | 0.0 |
| Ethiopia | 1 | 0.1 | 0.1 |
| Georgia Good Hope Walton County | 1 | 0.1 | 0.1 |
| Ghana | 1 | 0.1 | 0.1 |
| Guyana | 3 | 0.2 | 0.2 |
| Guyana: South America | 1 | 0.1 | 0.1 |
| Haiti | 4 | 0.2 | 0.2 |
| Jamaica | 7 | 0.4 | 0.4 |
| JAMAICA | 1 | 0.1 | 0.1 |
| Jamaica BWI Kingston | 1 | 0.1 | 0.1 |
| Jamaica WI | 0 | 0.0 | 0.0 |
| Japan | 1 | 0.1 | 0.1 |
| LA | 0 | 0.0 | 0.0 |
| Lamar County, GA | 1 | 0.1 | 0.1 |
| Macon County | 1 | 0.1 | 0.1 |
| Mexico | 0 | 0.0 | 0.0 |
| Mississippi | 1 | 0.1 | 0.1 |
| Montserrat British VI | 1 | 0.1 | 0.1 |
| “NA” | 1716 | 97.8 | 97.8 |
| Nassau Bahamas | 1 | 0.1 | 0.1 |
| Nigeria | 2 | 0.1 | 0.1 |
| Nigeria. | 0 | 0.0 | 0.0 |
| No biological info, I was adopted. | 1 | 0.1 | 0.1 |
| Oklahoma | 0 | 0.0 | 0.0 |
| Panama | 1 | 0.1 | 0.1 |
| Panama City of Panama | 0 | 0.0 | 0.0 |
| Puerto Rican | 1 | 0.1 | 0.1 |
| Sierre Leone | 0 | 0.0 | 0.0 |
| Trinidad | 1 | 0.1 | 0.1 |
| Trinidad and Tobago | 1 | 0.1 | 0.1 |
| Trinidad West Indies | 0 | 0.0 | 0.0 |
| Trinidad. | 0 | 0.0 | 0.0 |
| United States Texas | 0 | 0.0 | 0.0 |
| Venezuela | 0 | 0.0 | 0.0 |
| west Indies | 1 | 0.1 | 0.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| US | 15 | 93.8 | 93.8 |
| Africa | 0 | 0.0 | 0.0 |
| Cuba_Caribbean | 1 | 6.2 | 6.2 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Achtal, Bavaria, Germany | 0 | 0 | 0 |
| Barbados | 0 | 0 | 0 |
| Belize | 0 | 0 | 0 |
| Belize Central America | 0 | 0 | 0 |
| Belize, Central America | 0 | 0 | 0 |
| Bremont, TX | 0 | 0 | 0 |
| Buffalo NY | 0 | 0 | 0 |
| Canada. | 0 | 0 | 0 |
| Central America (Colon, Panama) | 0 | 0 | 0 |
| England | 0 | 0 | 0 |
| Ethiopia | 0 | 0 | 0 |
| Georgia Good Hope Walton County | 0 | 0 | 0 |
| Ghana | 0 | 0 | 0 |
| Guyana | 0 | 0 | 0 |
| Guyana: South America | 0 | 0 | 0 |
| Haiti | 0 | 0 | 0 |
| Jamaica | 0 | 0 | 0 |
| JAMAICA | 0 | 0 | 0 |
| Jamaica BWI Kingston | 0 | 0 | 0 |
| Jamaica WI | 0 | 0 | 0 |
| Japan | 0 | 0 | 0 |
| LA | 0 | 0 | 0 |
| Lamar County, GA | 0 | 0 | 0 |
| Macon County | 0 | 0 | 0 |
| Mexico | 0 | 0 | 0 |
| Mississippi | 0 | 0 | 0 |
| Montserrat British VI | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Nassau Bahamas | 0 | 0 | 0 |
| Nigeria | 0 | 0 | 0 |
| Nigeria. | 0 | 0 | 0 |
| No biological info, I was adopted. | 0 | 0 | 0 |
| Oklahoma | 0 | 0 | 0 |
| Panama | 0 | 0 | 0 |
| Panama City of Panama | 0 | 0 | 0 |
| Puerto Rican | 0 | 0 | 0 |
| Sierre Leone | 0 | 0 | 0 |
| Trinidad | 0 | 0 | 0 |
| Trinidad and Tobago | 0 | 0 | 0 |
| Trinidad West Indies | 0 | 0 | 0 |
| Trinidad. | 0 | 0 | 0 |
| United States Texas | 0 | 0 | 0 |
| Venezuela | 0 | 0 | 0 |
| west Indies | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
a8 <- as.factor(d[,"a8"])
levels(a8) <- list(less_or_15="1",
years_16_25="2",
more_than_25_or_whole_life= "3",
Scantron_Error="*")
a8 <- ordered(a8, c("less_or_15","years_16_25","more_than_25_or_whole_life","Scantron_Error"))
new.d <- data.frame(new.d, a8)
new.d <- apply_labels(new.d, a8 = "Years lived in the US")
temp.d <- data.frame (new.d, a8)
result<-questionr::freq(temp.d$a8, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "A8")
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 25 | 0.7 | 0.7 |
| years_16_25 | 52 | 1.5 | 1.5 |
| more_than_25_or_whole_life | 3400 | 95.6 | 97.8 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 79 | 2.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 2 | 0.6 | 0.6 |
| years_16_25 | 3 | 0.9 | 0.9 |
| more_than_25_or_whole_life | 315 | 98.1 | 98.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.3 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 4 | 1.9 | 1.9 |
| years_16_25 | 4 | 1.9 | 1.9 |
| more_than_25_or_whole_life | 198 | 94.3 | 96.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 6 | 1.9 | 2.0 |
| years_16_25 | 4 | 1.3 | 1.3 |
| more_than_25_or_whole_life | 297 | 94.3 | 96.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 0 | 0.0 | 0.0 |
| years_16_25 | 2 | 0.6 | 0.6 |
| more_than_25_or_whole_life | 342 | 96.1 | 99.1 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 11 | 3.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 0 | 0.0 | 0.0 |
| years_16_25 | 4 | 0.7 | 0.7 |
| more_than_25_or_whole_life | 571 | 97.6 | 99.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 1.7 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 13 | 0.7 | 0.8 |
| years_16_25 | 35 | 2.0 | 2.0 |
| more_than_25_or_whole_life | 1661 | 94.7 | 97.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 45 | 2.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| less_or_15 | 0 | 0 | 0 |
| years_16_25 | 0 | 0 | 0 |
| more_than_25_or_whole_life | 16 | 100 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
# B1Aa: Father: Has this person had prostate cancer?
b1aa <- as.factor(d[,"b1aa"])
levels(b1aa) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1aa <- ordered(b1aa, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1aa)
new.d <- apply_labels(new.d, b1aa = "Father")
temp.d <- data.frame (new.d, b1aa)
result<-questionr::freq(temp.d$b1aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Aa: Father: Has this person had prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 1979 | 55.6 | 58.2 |
| Yes | 649 | 18.2 | 19.1 |
| Dont_know | 772 | 21.7 | 22.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 157 | 4.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Ab: Father: Was he (or any) diagnosed BEFORE age 55?
b1ab <- as.factor(d[,"b1ab"])
levels(b1ab) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ab <- ordered(b1ab, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ab)
new.d <- apply_labels(new.d, b1ab = "Father")
temp.d <- data.frame (new.d, b1ab)
result<-questionr::freq(temp.d$b1ab,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ab: Father: Was he (or any) diagnosed BEFORE age 55?")
| n | % | val% | |
|---|---|---|---|
| No | 692 | 19.5 | 58.4 |
| Yes | 82 | 2.3 | 6.9 |
| Dont_know | 408 | 11.5 | 34.5 |
| Scantron_Error | 2 | 0.1 | 0.2 |
| NA | 2373 | 66.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Ac: Father: Did he (or any) die of prostate cancer?
b1ac <- as.factor(d[,"b1ac"])
levels(b1ac) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ac <- ordered(b1ac, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ac)
new.d <- apply_labels(new.d, b1ac = "Father")
temp.d <- data.frame (new.d, b1ac)
result<-questionr::freq(temp.d$b1ac,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ac: Father: Did he (or any) die of prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 755 | 21.2 | 62.8 |
| Yes | 224 | 6.3 | 18.6 |
| Dont_know | 223 | 6.3 | 18.5 |
| Scantron_Error | 1 | 0.0 | 0.1 |
| NA | 2354 | 66.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 203 | 63.2 | 64.2 |
| Yes | 51 | 15.9 | 16.1 |
| Dont_know | 62 | 19.3 | 19.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 54 | 16.8 | 56.2 |
| Yes | 5 | 1.6 | 5.2 |
| Dont_know | 37 | 11.5 | 38.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 225 | 70.1 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 61 | 19.0 | 64.2 |
| Yes | 15 | 4.7 | 15.8 |
| Dont_know | 18 | 5.6 | 18.9 |
| Scantron_Error | 1 | 0.3 | 1.1 |
| NA | 226 | 70.4 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 112 | 53.3 | 56.3 |
| Yes | 48 | 22.9 | 24.1 |
| Dont_know | 39 | 18.6 | 19.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 5.2 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 43 | 20.5 | 65.2 |
| Yes | 5 | 2.4 | 7.6 |
| Dont_know | 18 | 8.6 | 27.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 144 | 68.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 39 | 18.6 | 59.1 |
| Yes | 14 | 6.7 | 21.2 |
| Dont_know | 13 | 6.2 | 19.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 144 | 68.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 159 | 50.5 | 52.8 |
| Yes | 64 | 20.3 | 21.3 |
| Dont_know | 78 | 24.8 | 25.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 67 | 21.3 | 62.6 |
| Yes | 6 | 1.9 | 5.6 |
| Dont_know | 34 | 10.8 | 31.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 208 | 66.0 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 71 | 22.5 | 64.5 |
| Yes | 28 | 8.9 | 25.5 |
| Dont_know | 11 | 3.5 | 10.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 205 | 65.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 204 | 57.3 | 59.8 |
| Yes | 64 | 18.0 | 18.8 |
| Dont_know | 73 | 20.5 | 21.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 68 | 19.1 | 57.6 |
| Yes | 9 | 2.5 | 7.6 |
| Dont_know | 41 | 11.5 | 34.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 238 | 66.9 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 81 | 22.8 | 68.1 |
| Yes | 21 | 5.9 | 17.6 |
| Dont_know | 17 | 4.8 | 14.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 237 | 66.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 338 | 57.8 | 60.6 |
| Yes | 106 | 18.1 | 19.0 |
| Dont_know | 114 | 19.5 | 20.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 27 | 4.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 117 | 20.0 | 57.4 |
| Yes | 14 | 2.4 | 6.9 |
| Dont_know | 72 | 12.3 | 35.3 |
| Scantron_Error | 1 | 0.2 | 0.5 |
| NA | 381 | 65.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 130 | 22.2 | 62.5 |
| Yes | 37 | 6.3 | 17.8 |
| Dont_know | 41 | 7.0 | 19.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 377 | 64.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 957 | 54.6 | 57.3 |
| Yes | 309 | 17.6 | 18.5 |
| Dont_know | 403 | 23.0 | 24.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 85 | 4.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 336 | 19.2 | 57.6 |
| Yes | 41 | 2.3 | 7.0 |
| Dont_know | 205 | 11.7 | 35.2 |
| Scantron_Error | 1 | 0.1 | 0.2 |
| NA | 1171 | 66.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 366 | 20.9 | 61.5 |
| Yes | 106 | 6.0 | 17.8 |
| Dont_know | 123 | 7.0 | 20.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1159 | 66.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 6 | 37.5 | 37.5 |
| Yes | 7 | 43.8 | 43.8 |
| Dont_know | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 7 | 43.8 | 70 |
| Yes | 2 | 12.5 | 20 |
| Dont_know | 1 | 6.2 | 10 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 6 | 37.5 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 7 | 43.8 | 70 |
| Yes | 3 | 18.8 | 30 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 6 | 37.5 | NA |
| Total | 16 | 100.0 | 100 |
# B1BNo: Any Brother
b1bno <- as.factor(d[,"b1bno"])
levels(b1bno) <- list(No_brothers="1",
Scantron_Error="*")
new.d <- data.frame(new.d, b1bno)
new.d <- apply_labels(new.d, b1bno = "Any Brother")
temp.d <- data.frame (new.d, b1bno)
result<-questionr::freq(temp.d$b1bno,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1BNo: Any Brother")
| n | % | val% | |
|---|---|---|---|
| No_brothers | 321 | 9 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3236 | 91 | NA |
| Total | 3557 | 100 | 100 |
#B1Ba: Any Brother: Has this person had prostate cancer?
b1ba <- as.factor(d[,"b1ba"])
levels(b1ba) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ba <- ordered(b1ba, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ba)
new.d <- apply_labels(new.d, b1ba = "Any Brother: have p cancer")
temp.d <- data.frame (new.d, b1ba)
result<-questionr::freq(temp.d$b1ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ba: Any Brother: Has this person had prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 2110 | 59.3 | 66.8 |
| Yes | 708 | 19.9 | 22.4 |
| Dont_know | 338 | 9.5 | 10.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 399 | 11.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Ba2: Any Brother: If Yes, number with prostate cancer
b1ba2 <- as.factor(d[,"b1ba2"])
levels(b1ba2) <- list(One="1",
Two_or_more="2",
Scantron_Error="*")
b1ba2 <- ordered(b1ba2, c("One","Two_or_more","Scantron_Error"))
new.d <- data.frame(new.d, b1ba2)
new.d <- apply_labels(new.d, b1ba2 = "Number of brother")
temp.d <- data.frame (new.d, b1ba2)
result<-questionr::freq(temp.d$b1ba2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ba2: Any Brother: If Yes, number with prostate cancer")
| n | % | val% | |
|---|---|---|---|
| One | 288 | 8.1 | 63.2 |
| Two_or_more | 167 | 4.7 | 36.6 |
| Scantron_Error | 1 | 0.0 | 0.2 |
| NA | 3101 | 87.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Bb: Any Brother: Was he (or any) diagnosed BEFORE age 55?
b1bb <- as.factor(d[,"b1bb"])
levels(b1bb) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1bb <- ordered(b1bb, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1bb)
new.d <- apply_labels(new.d, b1bb = "Any Brother: before 55")
temp.d <- data.frame (new.d, b1bb)
result<-questionr::freq(temp.d$b1bb,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Bb: Any Brother: Was he (or any) diagnosed BEFORE age 55?")
| n | % | val% | |
|---|---|---|---|
| No | 685 | 19.3 | 62.8 |
| Yes | 167 | 4.7 | 15.3 |
| Dont_know | 239 | 6.7 | 21.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2466 | 69.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Bc: Any Brother: Did he (or any) die of prostate cancer?
b1bc <- as.factor(d[,"b1bc"])
levels(b1bc) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1bc <- ordered(b1bc, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1bc)
new.d <- apply_labels(new.d, b1bc = "Any Brother: die")
temp.d <- data.frame (new.d, b1bc)
result<-questionr::freq(temp.d$b1bc,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Bc: Any Brother: Did he (or any) die of prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 873 | 24.5 | 81.4 |
| Yes | 84 | 2.4 | 7.8 |
| Dont_know | 115 | 3.2 | 10.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2485 | 69.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 29 | 9 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 292 | 91 | NA |
| Total | 321 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 201 | 62.6 | 67.7 |
| Yes | 70 | 21.8 | 23.6 |
| Dont_know | 26 | 8.1 | 8.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.5 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 26 | 8.1 | 65 |
| Two_or_more | 14 | 4.4 | 35 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 281 | 87.5 | NA |
| Total | 321 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 59 | 18.4 | 62.1 |
| Yes | 18 | 5.6 | 18.9 |
| Dont_know | 18 | 5.6 | 18.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 226 | 70.4 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 80 | 24.9 | 84.2 |
| Yes | 7 | 2.2 | 7.4 |
| Dont_know | 8 | 2.5 | 8.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 226 | 70.4 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 32 | 15.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 178 | 84.8 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 120 | 57.1 | 69.0 |
| Yes | 28 | 13.3 | 16.1 |
| Dont_know | 26 | 12.4 | 14.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 17.1 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 19 | 9.0 | 79.2 |
| Two_or_more | 4 | 1.9 | 16.7 |
| Scantron_Error | 1 | 0.5 | 4.2 |
| NA | 186 | 88.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 28 | 13.3 | 57.1 |
| Yes | 7 | 3.3 | 14.3 |
| Dont_know | 14 | 6.7 | 28.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 161 | 76.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 35 | 16.7 | 76.1 |
| Yes | 1 | 0.5 | 2.2 |
| Dont_know | 10 | 4.8 | 21.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 164 | 78.1 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 28 | 8.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 287 | 91.1 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 177 | 56.2 | 63.9 |
| Yes | 72 | 22.9 | 26.0 |
| Dont_know | 28 | 8.9 | 10.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 38 | 12.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 30 | 9.5 | 65.2 |
| Two_or_more | 16 | 5.1 | 34.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 269 | 85.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 63 | 20.0 | 60.0 |
| Yes | 24 | 7.6 | 22.9 |
| Dont_know | 18 | 5.7 | 17.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 210 | 66.7 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 81 | 25.7 | 81 |
| Yes | 13 | 4.1 | 13 |
| Dont_know | 6 | 1.9 | 6 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 215 | 68.3 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 35 | 9.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 321 | 90.2 | NA |
| Total | 356 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 216 | 60.7 | 69.2 |
| Yes | 64 | 18.0 | 20.5 |
| Dont_know | 32 | 9.0 | 10.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 44 | 12.4 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 26 | 7.3 | 61.9 |
| Two_or_more | 16 | 4.5 | 38.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 314 | 88.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 63 | 17.7 | 58.9 |
| Yes | 14 | 3.9 | 13.1 |
| Dont_know | 30 | 8.4 | 28.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 249 | 69.9 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 83 | 23.3 | 79.8 |
| Yes | 10 | 2.8 | 9.6 |
| Dont_know | 11 | 3.1 | 10.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 252 | 70.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 31 | 5.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 554 | 94.7 | NA |
| Total | 585 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 373 | 63.8 | 68.7 |
| Yes | 114 | 19.5 | 21.0 |
| Dont_know | 56 | 9.6 | 10.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 42 | 7.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 42 | 7.2 | 60.9 |
| Two_or_more | 27 | 4.6 | 39.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 516 | 88.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 138 | 23.6 | 69.3 |
| Yes | 26 | 4.4 | 13.1 |
| Dont_know | 35 | 6.0 | 17.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 386 | 66.0 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 161 | 27.5 | 84.3 |
| Yes | 10 | 1.7 | 5.2 |
| Dont_know | 20 | 3.4 | 10.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 394 | 67.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 163 | 9.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1591 | 90.7 | NA |
| Total | 1754 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1015 | 57.9 | 65.8 |
| Yes | 356 | 20.3 | 23.1 |
| Dont_know | 169 | 9.6 | 11.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 212 | 12.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 144 | 8.2 | 61.5 |
| Two_or_more | 90 | 5.1 | 38.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1520 | 86.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 331 | 18.9 | 62.3 |
| Yes | 76 | 4.3 | 14.3 |
| Dont_know | 124 | 7.1 | 23.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1223 | 69.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 428 | 24.4 | 80.8 |
| Yes | 43 | 2.5 | 8.1 |
| Dont_know | 59 | 3.4 | 11.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1224 | 69.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 3 | 18.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 8 | 50.0 | 61.5 |
| Yes | 4 | 25.0 | 30.8 |
| Dont_know | 1 | 6.2 | 7.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 18.8 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 1 | 6.2 | 100 |
| Two_or_more | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 3 | 18.8 | 60 |
| Yes | 2 | 12.5 | 40 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 5 | 31.2 | 83.3 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 1 | 6.2 | 16.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 62.5 | NA |
| Total | 16 | 100.0 | 100.0 |
# B1BNo
b1cno <- as.factor(d[,"b1cno"])
levels(b1cno) <- list(No_brothers="1",
Scantron_Error="*")
new.d <- data.frame(new.d, b1cno)
new.d <- apply_labels(new.d, b1cno = "Any Son")
temp.d <- data.frame (new.d, b1cno)
result<-questionr::freq(temp.d$b1cno,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1CNo: Any Son")
| n | % | val% | |
|---|---|---|---|
| No_brothers | 608 | 17.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2949 | 82.9 | NA |
| Total | 3557 | 100.0 | 100 |
#B1Ca
b1ca <- as.factor(d[,"b1ca"])
levels(b1ca) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ca <- ordered(b1ca, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ca)
new.d <- apply_labels(new.d, b1ca = "Any Son: have p cancer")
temp.d <- data.frame (new.d, b1ca)
result<-questionr::freq(temp.d$b1ca,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ca: Any Son: Has this person had prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 2621 | 73.7 | 93.2 |
| Yes | 87 | 2.4 | 3.1 |
| Dont_know | 104 | 2.9 | 3.7 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 744 | 20.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Ca2
b1ca2 <- as.factor(d[,"b1ca2"])
levels(b1ca2) <- list(One="1",
Two_or_more="2",
Scantron_Error="*")
b1ca2 <- ordered(b1ca2, c("One","Two_or_more","Scantron_Error"))
new.d <- data.frame(new.d, b1ca2)
new.d <- apply_labels(new.d, b1ca2 = "Number of sons")
temp.d <- data.frame (new.d, b1ca2)
result<-questionr::freq(temp.d$b1ca2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ca2: Any Son: If Yes, number with prostate cancer")
| n | % | val% | |
|---|---|---|---|
| One | 33 | 0.9 | 48.5 |
| Two_or_more | 34 | 1.0 | 50.0 |
| Scantron_Error | 1 | 0.0 | 1.5 |
| NA | 3489 | 98.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Cb
b1cb <- as.factor(d[,"b1cb"])
levels(b1cb) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1cb <- ordered(b1cb, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1cb)
new.d <- apply_labels(new.d, b1cb = "Any Son: before 55")
temp.d <- data.frame (new.d, b1cb)
result<-questionr::freq(temp.d$b1cb,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Cb: Any Son: Was he (or any) diagnosed BEFORE age 55?")
| n | % | val% | |
|---|---|---|---|
| No | 508 | 14.3 | 85.1 |
| Yes | 12 | 0.3 | 2.0 |
| Dont_know | 77 | 2.2 | 12.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2960 | 83.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#B1Cc
b1cc <- as.factor(d[,"b1cc"])
levels(b1cc) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1cc <- ordered(b1cc, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1cc)
new.d <- apply_labels(new.d, b1cc = "Any Son: die")
temp.d <- data.frame (new.d, b1cc)
result<-questionr::freq(temp.d$b1cc,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Cc: Any Son: Did he (or any) die of prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 518 | 14.6 | 88.5 |
| Yes | 3 | 0.1 | 0.5 |
| Dont_know | 64 | 1.8 | 10.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2972 | 83.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 46 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 275 | 85.7 | NA |
| Total | 321 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 260 | 81.0 | 96.3 |
| Yes | 3 | 0.9 | 1.1 |
| Dont_know | 7 | 2.2 | 2.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 51 | 15.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 3 | 0.9 | 42.9 |
| Two_or_more | 4 | 1.2 | 57.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 314 | 97.8 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 34 | 10.6 | 77.3 |
| Yes | 2 | 0.6 | 4.5 |
| Dont_know | 8 | 2.5 | 18.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 277 | 86.3 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 33 | 10.3 | 84.6 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 6 | 1.9 | 15.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 282 | 87.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 47 | 22.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 163 | 77.6 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 145 | 69.0 | 95.4 |
| Yes | 4 | 1.9 | 2.6 |
| Dont_know | 3 | 1.4 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 58 | 27.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 3 | 1.4 | 42.9 |
| Two_or_more | 4 | 1.9 | 57.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 203 | 96.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 19 | 9.0 | 79.2 |
| Yes | 1 | 0.5 | 4.2 |
| Dont_know | 4 | 1.9 | 16.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 186 | 88.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 20 | 9.5 | 87.0 |
| Yes | 1 | 0.5 | 4.3 |
| Dont_know | 2 | 1.0 | 8.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 187 | 89.0 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 53 | 16.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 262 | 83.2 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 237 | 75.2 | 92.2 |
| Yes | 10 | 3.2 | 3.9 |
| Dont_know | 10 | 3.2 | 3.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 58 | 18.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 2 | 0.6 | 50 |
| Two_or_more | 2 | 0.6 | 50 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 311 | 98.7 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 50 | 15.9 | 92.6 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 4 | 1.3 | 7.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 261 | 82.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 49 | 15.6 | 94.2 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 3 | 1.0 | 5.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 263 | 83.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 71 | 19.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 285 | 80.1 | NA |
| Total | 356 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 254 | 71.3 | 94.1 |
| Yes | 8 | 2.2 | 3.0 |
| Dont_know | 8 | 2.2 | 3.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 86 | 24.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 3 | 0.8 | 75 |
| Two_or_more | 1 | 0.3 | 25 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 352 | 98.9 | NA |
| Total | 356 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 48 | 13.5 | 87.3 |
| Yes | 1 | 0.3 | 1.8 |
| Dont_know | 6 | 1.7 | 10.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 301 | 84.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 49 | 13.8 | 89.1 |
| Yes | 1 | 0.3 | 1.8 |
| Dont_know | 5 | 1.4 | 9.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 301 | 84.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 82 | 14 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 503 | 86 | NA |
| Total | 585 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 443 | 75.7 | 93.1 |
| Yes | 15 | 2.6 | 3.2 |
| Dont_know | 18 | 3.1 | 3.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 109 | 18.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 4 | 0.7 | 40 |
| Two_or_more | 5 | 0.9 | 50 |
| Scantron_Error | 1 | 0.2 | 10 |
| NA | 575 | 98.3 | NA |
| Total | 585 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 95 | 16.2 | 84.8 |
| Yes | 1 | 0.2 | 0.9 |
| Dont_know | 16 | 2.7 | 14.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 473 | 80.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 94 | 16.1 | 86.2 |
| Yes | 1 | 0.2 | 0.9 |
| Dont_know | 14 | 2.4 | 12.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 476 | 81.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 306 | 17.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1448 | 82.6 | NA |
| Total | 1754 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1270 | 72.4 | 92.3 |
| Yes | 47 | 2.7 | 3.4 |
| Dont_know | 58 | 3.3 | 4.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 378 | 21.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| One | 18 | 1.0 | 50 |
| Two_or_more | 18 | 1.0 | 50 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1718 | 97.9 | NA |
| Total | 1754 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 259 | 14.8 | 84.9 |
| Yes | 7 | 0.4 | 2.3 |
| Dont_know | 39 | 2.2 | 12.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1449 | 82.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 270 | 15.4 | 88.8 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 34 | 1.9 | 11.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1450 | 82.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No_brothers | 3 | 18.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 12 | 75 | 100 |
| Yes | 0 | 0 | 0 |
| Dont_know | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 4 | 25 | NA |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| One | 0 | 0 | NaN |
| Two_or_more | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 3 | 18.8 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 3 | 18.8 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
# B1Da: Maternal Grandfather (Mom’s side): Has this person had prostate cancer?
b1da <- as.factor(d[,"b1da"])
levels(b1da) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1da <- ordered(b1da, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1da)
new.d <- apply_labels(new.d, b1da = "Father")
temp.d <- data.frame (new.d, b1da)
result<-questionr::freq(temp.d$b1da,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Da: Maternal Grandfather (Mom’s side): Has this person had prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 1474 | 41.4 | 44.6 |
| Yes | 104 | 2.9 | 3.1 |
| Dont_know | 1726 | 48.5 | 52.2 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 249 | 7.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
# B1Db: Maternal Grandfather (Mom’s side): Was he (or any) diagnosed BEFORE age 55?
b1db <- as.factor(d[,"b1db"])
levels(b1db) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1db <- ordered(b1db, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1db)
new.d <- apply_labels(new.d, b1db = "Father")
temp.d <- data.frame (new.d, b1db)
result<-questionr::freq(temp.d$b1db,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Db: Maternal Grandfather (Mom’s side): Was he (or any) diagnosed BEFORE age 55?")
| n | % | val% | |
|---|---|---|---|
| No | 286 | 8.0 | 38.2 |
| Yes | 10 | 0.3 | 1.3 |
| Dont_know | 452 | 12.7 | 60.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2809 | 79.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
# B1Dc: Maternal Grandfather (Mom’s side): Did he (or any) die of prostate cancer?
b1dc <- as.factor(d[,"b1dc"])
levels(b1dc) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1dc <- ordered(b1dc, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1dc)
new.d <- apply_labels(new.d, b1dc = "Father")
temp.d <- data.frame (new.d, b1dc)
result<-questionr::freq(temp.d$b1dc,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Dc: Maternal Grandfather (Mom’s side): Did he (or any) die of prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 292 | 8.2 | 38.5 |
| Yes | 42 | 1.2 | 5.5 |
| Dont_know | 425 | 11.9 | 56.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2798 | 78.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 161 | 50.2 | 51.8 |
| Yes | 6 | 1.9 | 1.9 |
| Dont_know | 143 | 44.5 | 46.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 17 | 5.3 | 29.8 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 40 | 12.5 | 70.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 264 | 82.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 17 | 5.3 | 28.8 |
| Yes | 3 | 0.9 | 5.1 |
| Dont_know | 39 | 12.1 | 66.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 262 | 81.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 67 | 31.9 | 34.9 |
| Yes | 6 | 2.9 | 3.1 |
| Dont_know | 119 | 56.7 | 62.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 8.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 12 | 5.7 | 36.4 |
| Yes | 1 | 0.5 | 3.0 |
| Dont_know | 20 | 9.5 | 60.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 177 | 84.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 6.2 | 39.4 |
| Yes | 2 | 1.0 | 6.1 |
| Dont_know | 18 | 8.6 | 54.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 177 | 84.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 127 | 40.3 | 42.5 |
| Yes | 10 | 3.2 | 3.3 |
| Dont_know | 162 | 51.4 | 54.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 30 | 9.5 | 42.3 |
| Yes | 1 | 0.3 | 1.4 |
| Dont_know | 40 | 12.7 | 56.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 244 | 77.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 31 | 9.8 | 44.9 |
| Yes | 6 | 1.9 | 8.7 |
| Dont_know | 32 | 10.2 | 46.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 246 | 78.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 151 | 42.4 | 45.2 |
| Yes | 16 | 4.5 | 4.8 |
| Dont_know | 166 | 46.6 | 49.7 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 22 | 6.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 28 | 7.9 | 40.6 |
| Yes | 2 | 0.6 | 2.9 |
| Dont_know | 39 | 11.0 | 56.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 287 | 80.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 29 | 8.1 | 42.0 |
| Yes | 4 | 1.1 | 5.8 |
| Dont_know | 36 | 10.1 | 52.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 287 | 80.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 261 | 44.6 | 49.1 |
| Yes | 21 | 3.6 | 3.9 |
| Dont_know | 250 | 42.7 | 47.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 53 | 9.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 58 | 9.9 | 40.0 |
| Yes | 3 | 0.5 | 2.1 |
| Dont_know | 84 | 14.4 | 57.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 440 | 75.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 56 | 9.6 | 39.2 |
| Yes | 9 | 1.5 | 6.3 |
| Dont_know | 78 | 13.3 | 54.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 442 | 75.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 703 | 40.1 | 43.3 |
| Yes | 44 | 2.5 | 2.7 |
| Dont_know | 876 | 49.9 | 53.9 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 129 | 7.4 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 140 | 8.0 | 38.0 |
| Yes | 2 | 0.1 | 0.5 |
| Dont_know | 226 | 12.9 | 61.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1386 | 79.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 145 | 8.3 | 38.1 |
| Yes | 18 | 1.0 | 4.7 |
| Dont_know | 218 | 12.4 | 57.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1373 | 78.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 4 | 25.0 | 26.7 |
| Yes | 1 | 6.2 | 6.7 |
| Dont_know | 10 | 62.5 | 66.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 20 |
| Yes | 1 | 6.2 | 20 |
| Dont_know | 3 | 18.8 | 60 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 20 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 4 | 25.0 | 80 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
# B1Ea: Paternal Grandfather (Dad’s side): Has this person had prostate cancer?
b1ea <- as.factor(d[,"b1ea"])
levels(b1ea) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ea <- ordered(b1ea, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ea)
new.d <- apply_labels(new.d, b1ea = "Father")
temp.d <- data.frame (new.d, b1ea)
result<-questionr::freq(temp.d$b1ea,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ea: Paternal Grandfather (Dad’s side): Has this person had prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 1327 | 37.3 | 40.5 |
| Yes | 97 | 2.7 | 3.0 |
| Dont_know | 1851 | 52.0 | 56.5 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 281 | 7.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
# B1Eb: Paternal Grandfather (Dad’s side): Was he (or any) diagnosed BEFORE age 55?
b1eb <- as.factor(d[,"b1eb"])
levels(b1eb) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1eb <- ordered(b1eb, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1eb)
new.d <- apply_labels(new.d, b1eb = "Father")
temp.d <- data.frame (new.d, b1eb)
result<-questionr::freq(temp.d$b1eb,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Eb: Paternal Grandfather (Dad’s side): Was he (or any) diagnosed BEFORE age 55?")
| n | % | val% | |
|---|---|---|---|
| No | 241 | 6.8 | 33.1 |
| Yes | 15 | 0.4 | 2.1 |
| Dont_know | 472 | 13.3 | 64.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2829 | 79.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
# B1Ec: Paternal Grandfather (Dad’s side): Did he (or any) die of prostate cancer?
b1ec <- as.factor(d[,"b1ec"])
levels(b1ec) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
b1ec <- ordered(b1ec, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, b1ec)
new.d <- apply_labels(new.d, b1ec = "Father")
temp.d <- data.frame (new.d, b1ec)
result<-questionr::freq(temp.d$b1ec,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "B1Ec: Paternal Grandfather (Dad’s side): Did he (or any) die of prostate cancer?")
| n | % | val% | |
|---|---|---|---|
| No | 256 | 7.2 | 34.2 |
| Yes | 47 | 1.3 | 6.3 |
| Dont_know | 446 | 12.5 | 59.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2808 | 78.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 146 | 45.5 | 47.7 |
| Yes | 9 | 2.8 | 2.9 |
| Dont_know | 151 | 47.0 | 49.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.7 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 18 | 5.6 | 31.6 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 39 | 12.1 | 68.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 264 | 82.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 20 | 6.2 | 33.9 |
| Yes | 2 | 0.6 | 3.4 |
| Dont_know | 37 | 11.5 | 62.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 262 | 81.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 55 | 26.2 | 28.6 |
| Yes | 11 | 5.2 | 5.7 |
| Dont_know | 126 | 60.0 | 65.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 8.6 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 12 | 5.7 | 28.6 |
| Yes | 3 | 1.4 | 7.1 |
| Dont_know | 27 | 12.9 | 64.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 168 | 80.0 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 6.2 | 31.7 |
| Yes | 6 | 2.9 | 14.6 |
| Dont_know | 22 | 10.5 | 53.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 169 | 80.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 109 | 34.6 | 36.7 |
| Yes | 7 | 2.2 | 2.4 |
| Dont_know | 181 | 57.5 | 60.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 5.7 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 25 | 7.9 | 38.5 |
| Yes | 0 | 0.0 | 0.0 |
| Dont_know | 40 | 12.7 | 61.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 250 | 79.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 24 | 7.6 | 36.4 |
| Yes | 2 | 0.6 | 3.0 |
| Dont_know | 40 | 12.7 | 60.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 249 | 79.0 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 148 | 41.6 | 45.0 |
| Yes | 10 | 2.8 | 3.0 |
| Dont_know | 170 | 47.8 | 51.7 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 27 | 7.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 26 | 7.3 | 41.9 |
| Yes | 1 | 0.3 | 1.6 |
| Dont_know | 35 | 9.8 | 56.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 294 | 82.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 25 | 7.0 | 39.1 |
| Yes | 6 | 1.7 | 9.4 |
| Dont_know | 33 | 9.3 | 51.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 292 | 82.0 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 238 | 40.7 | 45.2 |
| Yes | 21 | 3.6 | 4.0 |
| Dont_know | 267 | 45.6 | 50.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 59 | 10.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 46 | 7.9 | 32.6 |
| Yes | 5 | 0.9 | 3.5 |
| Dont_know | 90 | 15.4 | 63.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 444 | 75.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 48 | 8.2 | 34.5 |
| Yes | 11 | 1.9 | 7.9 |
| Dont_know | 80 | 13.7 | 57.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 446 | 76.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 627 | 35.7 | 38.9 |
| Yes | 38 | 2.2 | 2.4 |
| Dont_know | 946 | 53.9 | 58.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 143 | 8.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 113 | 6.4 | 31.7 |
| Yes | 6 | 0.3 | 1.7 |
| Dont_know | 238 | 13.6 | 66.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1397 | 79.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 125 | 7.1 | 33.2 |
| Yes | 19 | 1.1 | 5.1 |
| Dont_know | 232 | 13.2 | 61.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1378 | 78.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 4 | 25.0 | 26.7 |
| Yes | 1 | 6.2 | 6.7 |
| Dont_know | 10 | 62.5 | 66.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 25 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 3 | 18.8 | 75 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 12 | 75.0 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 25 |
| Yes | 1 | 6.2 | 25 |
| Dont_know | 2 | 12.5 | 50 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 12 | 75.0 | NA |
| Total | 16 | 100.0 | 100 |
b3 <- as.factor(d[,"b3"])
levels(b3) <- list(Excellent="1",
Very_Good="2",
Good="3",
Fair="4",
Poor="5",
Scantron_Error="*")
b3 <- ordered(b3, c("Excellent","Very_Good","Good","Fair","Poor","Scantron_Error"))
new.d <- data.frame(new.d, b3)
new.d <- apply_labels(new.d, b3 = "Current Health")
temp.d <- data.frame (new.d, b3)
result<-questionr::freq(temp.d$b3, cum = TRUE, total = TRUE)
kable(result, format = "simple", align = 'l')
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 221 | 6.2 | 6.5 | 6.2 | 6.5 |
| Very_Good | 933 | 26.2 | 27.3 | 32.4 | 33.8 |
| Good | 1439 | 40.5 | 42.1 | 72.9 | 75.9 |
| Fair | 724 | 20.4 | 21.2 | 93.3 | 97.1 |
| Poor | 95 | 2.7 | 2.8 | 95.9 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 96.0 | 100.0 |
| NA | 142 | 4.0 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 27 | 8.4 | 8.7 | 8.4 | 8.7 |
| Very_Good | 102 | 31.8 | 32.7 | 40.2 | 41.3 |
| Good | 120 | 37.4 | 38.5 | 77.6 | 79.8 |
| Fair | 51 | 15.9 | 16.3 | 93.5 | 96.2 |
| Poor | 12 | 3.7 | 3.8 | 97.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.2 | 100.0 |
| NA | 9 | 2.8 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 14 | 6.7 | 7.0 | 6.7 | 7.0 |
| Very_Good | 61 | 29.0 | 30.7 | 35.7 | 37.7 |
| Good | 81 | 38.6 | 40.7 | 74.3 | 78.4 |
| Fair | 41 | 19.5 | 20.6 | 93.8 | 99.0 |
| Poor | 1 | 0.5 | 0.5 | 94.3 | 99.5 |
| Scantron_Error | 1 | 0.5 | 0.5 | 94.8 | 100.0 |
| NA | 11 | 5.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 21 | 6.7 | 7.0 | 6.7 | 7.0 |
| Very_Good | 92 | 29.2 | 30.5 | 35.9 | 37.4 |
| Good | 122 | 38.7 | 40.4 | 74.6 | 77.8 |
| Fair | 58 | 18.4 | 19.2 | 93.0 | 97.0 |
| Poor | 9 | 2.9 | 3.0 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 20 | 5.6 | 5.8 | 5.6 | 5.8 |
| Very_Good | 72 | 20.2 | 21.1 | 25.8 | 26.9 |
| Good | 145 | 40.7 | 42.4 | 66.6 | 69.3 |
| Fair | 87 | 24.4 | 25.4 | 91.0 | 94.7 |
| Poor | 17 | 4.8 | 5.0 | 95.8 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 96.1 | 100.0 |
| NA | 14 | 3.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 29 | 5.0 | 5.2 | 5.0 | 5.2 |
| Very_Good | 135 | 23.1 | 24.0 | 28.0 | 29.1 |
| Good | 236 | 40.3 | 41.9 | 68.4 | 71.0 |
| Fair | 144 | 24.6 | 25.6 | 93.0 | 96.6 |
| Poor | 19 | 3.2 | 3.4 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 22 | 3.8 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 109 | 6.2 | 6.5 | 6.2 | 6.5 |
| Very_Good | 466 | 26.6 | 27.7 | 32.8 | 34.2 |
| Good | 728 | 41.5 | 43.3 | 74.3 | 77.5 |
| Fair | 341 | 19.4 | 20.3 | 93.7 | 97.8 |
| Poor | 36 | 2.1 | 2.1 | 95.8 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 95.8 | 100.0 |
| NA | 73 | 4.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Excellent | 1 | 6.2 | 6.2 | 6.2 | 6.2 |
| Very_Good | 5 | 31.2 | 31.2 | 37.5 | 37.5 |
| Good | 7 | 43.8 | 43.8 | 81.2 | 81.2 |
| Fair | 2 | 12.5 | 12.5 | 93.8 | 93.8 |
| Poor | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
# Heart Attack
b4aa <- as.factor(d[,"b4aa"])
levels(b4aa) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4aa <- ordered(b4aa, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4aa)
new.d <- apply_labels(new.d, b4aa = "Heart Attack")
temp.d <- data.frame (new.d, b4aa)
result<-questionr::freq(temp.d$b4aa, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Heart Attack")
| n | % | val% | |
|---|---|---|---|
| No | 3110 | 87.4 | 92.8 |
| Yes | 238 | 6.7 | 7.1 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 207 | 5.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4ab <- as.factor(d[,"b4ab"])
new.d <- data.frame(new.d, b4ab)
new.d <- apply_labels(new.d, b4ab = "Heart Attack age")
temp.d <- data.frame (new.d, b4ab)
result<-questionr::freq(temp.d$b4ab, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Heart Attack Age")
| n | % | val% | |
|---|---|---|---|
| 0 | 43 | 1.2 | 1.2 |
| 1 | 1 | 0.0 | 0.0 |
| 14 | 1 | 0.0 | 0.0 |
| 17 | 2 | 0.1 | 0.1 |
| 20 | 1 | 0.0 | 0.0 |
| 24 | 1 | 0.0 | 0.0 |
| 25 | 2 | 0.1 | 0.1 |
| 26 | 1 | 0.0 | 0.0 |
| 27 | 2 | 0.1 | 0.1 |
| 29 | 2 | 0.1 | 0.1 |
| 31 | 2 | 0.1 | 0.1 |
| 32 | 1 | 0.0 | 0.0 |
| 34 | 1 | 0.0 | 0.0 |
| 35 | 2 | 0.1 | 0.1 |
| 38 | 3 | 0.1 | 0.1 |
| 40 | 4 | 0.1 | 0.1 |
| 42 | 1 | 0.0 | 0.0 |
| 44 | 2 | 0.1 | 0.1 |
| 45 | 4 | 0.1 | 0.1 |
| 46 | 4 | 0.1 | 0.1 |
| 47 | 1 | 0.0 | 0.0 |
| 48 | 7 | 0.2 | 0.2 |
| 49 | 2 | 0.1 | 0.1 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 19 | 0.5 | 0.5 |
| 51 | 6 | 0.2 | 0.2 |
| 52 | 10 | 0.3 | 0.3 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 5 | 0.1 | 0.1 |
| 55 | 10 | 0.3 | 0.3 |
| 56 | 4 | 0.1 | 0.1 |
| 57 | 7 | 0.2 | 0.2 |
| 58 | 12 | 0.3 | 0.3 |
| 59 | 12 | 0.3 | 0.3 |
| 60 | 14 | 0.4 | 0.4 |
| 61 | 6 | 0.2 | 0.2 |
| 62 | 3 | 0.1 | 0.1 |
| 63 | 8 | 0.2 | 0.2 |
| 64 | 8 | 0.2 | 0.2 |
| 65 | 6 | 0.2 | 0.2 |
| 66 | 3 | 0.1 | 0.1 |
| 67 | 6 | 0.2 | 0.2 |
| 68 | 2 | 0.1 | 0.1 |
| 69 | 7 | 0.2 | 0.2 |
| 70 | 5 | 0.1 | 0.1 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 1 | 0.0 | 0.0 |
| 73 | 3 | 0.1 | 0.1 |
| 74 | 6 | 0.2 | 0.2 |
| 76 | 2 | 0.1 | 0.1 |
| 79 | 1 | 0.0 | 0.0 |
| 93 | 1 | 0.0 | 0.0 |
| “NA” | 3294 | 92.6 | 92.6 |
| Total | 3557 | 100.0 | 100.0 |
# Heart Failure or CHF
b4ba <- as.factor(d[,"b4ba"])
levels(b4ba) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ba <- ordered(b4ba, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ba)
new.d <- apply_labels(new.d, b4ba = "Heart Failure or CHF")
temp.d <- data.frame (new.d, b4ba)
result<-questionr::freq(temp.d$b4ba, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Heart Failure or CHF")
| n | % | val% | |
|---|---|---|---|
| No | 3092 | 86.9 | 93.3 |
| Yes | 222 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 243 | 6.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4bb <- as.factor(d[,"b4bb"])
new.d <- data.frame(new.d, b4bb)
new.d <- apply_labels(new.d, b4bb = "Heart Failure or CHF age")
temp.d <- data.frame (new.d, b4bb)
result<-questionr::freq(temp.d$b4bb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Heart Failure or CHF Age")
| n | % | val% | |
|---|---|---|---|
| 12 | 1 | 0.0 | 0.0 |
| 13 | 1 | 0.0 | 0.0 |
| 17 | 1 | 0.0 | 0.0 |
| 18 | 1 | 0.0 | 0.0 |
| 20 | 2 | 0.1 | 0.1 |
| 25 | 1 | 0.0 | 0.0 |
| 27 | 1 | 0.0 | 0.0 |
| 28 | 1 | 0.0 | 0.0 |
| 29 | 1 | 0.0 | 0.0 |
| 30 | 2 | 0.1 | 0.1 |
| 31 | 1 | 0.0 | 0.0 |
| 34 | 1 | 0.0 | 0.0 |
| 35 | 1 | 0.0 | 0.0 |
| 39 | 1 | 0.0 | 0.0 |
| 40 | 4 | 0.1 | 0.1 |
| 42 | 1 | 0.0 | 0.0 |
| 43 | 3 | 0.1 | 0.1 |
| 45 | 1 | 0.0 | 0.0 |
| 46 | 2 | 0.1 | 0.1 |
| 47 | 2 | 0.1 | 0.1 |
| 48 | 4 | 0.1 | 0.1 |
| 49 | 6 | 0.2 | 0.2 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 6 | 0.2 | 0.2 |
| 51 | 3 | 0.1 | 0.1 |
| 52 | 7 | 0.2 | 0.2 |
| 53 | 4 | 0.1 | 0.1 |
| 54 | 5 | 0.1 | 0.1 |
| 55 | 9 | 0.3 | 0.3 |
| 56 | 10 | 0.3 | 0.3 |
| 57 | 4 | 0.1 | 0.1 |
| 58 | 6 | 0.2 | 0.2 |
| 59 | 10 | 0.3 | 0.3 |
| 60 | 11 | 0.3 | 0.3 |
| 61 | 6 | 0.2 | 0.2 |
| 62 | 11 | 0.3 | 0.3 |
| 63 | 6 | 0.2 | 0.2 |
| 64 | 4 | 0.1 | 0.1 |
| 65 | 8 | 0.2 | 0.2 |
| 66 | 5 | 0.1 | 0.1 |
| 67 | 4 | 0.1 | 0.1 |
| 68 | 5 | 0.1 | 0.1 |
| 69 | 5 | 0.1 | 0.1 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 6 | 0.2 | 0.2 |
| 71 | 5 | 0.1 | 0.1 |
| 72 | 3 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 3 | 0.1 | 0.1 |
| 75 | 2 | 0.1 | 0.1 |
| 77 | 1 | 0.0 | 0.0 |
| 78 | 1 | 0.0 | 0.0 |
| 80 | 1 | 0.0 | 0.0 |
| 82 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| “NA” | 3361 | 94.5 | 94.5 |
| Total | 3557 | 100.0 | 100.0 |
# Stroke
b4ca <- as.factor(d[,"b4ca"])
levels(b4ca) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ca <- ordered(b4ca, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ca)
new.d <- apply_labels(new.d, b4ca = "Stroke")
temp.d <- data.frame (new.d, b4ca)
result<-questionr::freq(temp.d$b4ca,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Stroke")
| n | % | val% | |
|---|---|---|---|
| No | 3009 | 84.6 | 90.7 |
| Yes | 306 | 8.6 | 9.2 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 239 | 6.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4cb <- as.factor(d[,"b4cb"])
new.d <- data.frame(new.d, b4cb)
new.d <- apply_labels(new.d, b4cb = "Stroke age")
temp.d <- data.frame (new.d, b4cb)
result<-questionr::freq(temp.d$b4cb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Stroke Age")
| n | % | val% | |
|---|---|---|---|
| 0 | 67 | 1.9 | 1.9 |
| 15 | 1 | 0.0 | 0.0 |
| 16 | 1 | 0.0 | 0.0 |
| 19 | 1 | 0.0 | 0.0 |
| 20 | 1 | 0.0 | 0.0 |
| 23 | 1 | 0.0 | 0.0 |
| 25 | 1 | 0.0 | 0.0 |
| 27 | 1 | 0.0 | 0.0 |
| 30 | 2 | 0.1 | 0.1 |
| 34 | 2 | 0.1 | 0.1 |
| 35 | 1 | 0.0 | 0.0 |
| 38 | 1 | 0.0 | 0.0 |
| 40 | 4 | 0.1 | 0.1 |
| 42 | 4 | 0.1 | 0.1 |
| 43 | 3 | 0.1 | 0.1 |
| 45 | 7 | 0.2 | 0.2 |
| 46 | 4 | 0.1 | 0.1 |
| 47 | 2 | 0.1 | 0.1 |
| 48 | 4 | 0.1 | 0.1 |
| 49 | 1 | 0.0 | 0.0 |
| 5 | 3 | 0.1 | 0.1 |
| 50 | 11 | 0.3 | 0.3 |
| 51 | 5 | 0.1 | 0.1 |
| 52 | 7 | 0.2 | 0.2 |
| 53 | 3 | 0.1 | 0.1 |
| 54 | 11 | 0.3 | 0.3 |
| 55 | 11 | 0.3 | 0.3 |
| 56 | 7 | 0.2 | 0.2 |
| 57 | 12 | 0.3 | 0.3 |
| 58 | 7 | 0.2 | 0.2 |
| 59 | 10 | 0.3 | 0.3 |
| 60 | 16 | 0.4 | 0.4 |
| 61 | 14 | 0.4 | 0.4 |
| 62 | 11 | 0.3 | 0.3 |
| 63 | 19 | 0.5 | 0.5 |
| 64 | 9 | 0.3 | 0.3 |
| 65 | 15 | 0.4 | 0.4 |
| 66 | 9 | 0.3 | 0.3 |
| 67 | 7 | 0.2 | 0.2 |
| 68 | 10 | 0.3 | 0.3 |
| 69 | 10 | 0.3 | 0.3 |
| 70 | 6 | 0.2 | 0.2 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 3 | 0.1 | 0.1 |
| 75 | 1 | 0.0 | 0.0 |
| 78 | 2 | 0.1 | 0.1 |
| 79 | 3 | 0.1 | 0.1 |
| 8 | 1 | 0.0 | 0.0 |
| “NA” | 3218 | 90.5 | 90.5 |
| Total | 3557 | 100.0 | 100.0 |
# Hypertension
b4da <- as.factor(d[,"b4da"])
levels(b4da) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4da <- ordered(b4da, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4da)
new.d <- apply_labels(new.d, b4da = "Hypertension")
temp.d <- data.frame (new.d, b4da)
result<-questionr::freq(temp.d$b4da, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Hypertension")
| n | % | val% | |
|---|---|---|---|
| No | 887 | 24.9 | 26.2 |
| Yes | 2496 | 70.2 | 73.6 |
| Scantron_Error | 7 | 0.2 | 0.2 |
| NA | 167 | 4.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4db <- as.factor(d[,"b4db"])
new.d <- data.frame(new.d, b4db)
new.d <- apply_labels(new.d, b4db = "Hypertension age")
temp.d <- data.frame (new.d, b4db)
result<-questionr::freq(temp.d$b4db, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Hypertension Age")
| n | % | val% | |
|---|---|---|---|
| .35 | 1 | 0.0 | 0.0 |
| 1 | 1 | 0.0 | 0.0 |
| 10 | 1 | 0.0 | 0.0 |
| 12 | 3 | 0.1 | 0.1 |
| 13 | 1 | 0.0 | 0.0 |
| 14 | 1 | 0.0 | 0.0 |
| 15 | 3 | 0.1 | 0.1 |
| 16 | 9 | 0.3 | 0.3 |
| 17 | 2 | 0.1 | 0.1 |
| 18 | 7 | 0.2 | 0.2 |
| 19 | 4 | 0.1 | 0.1 |
| 2 | 3 | 0.1 | 0.1 |
| 20 | 12 | 0.3 | 0.3 |
| 21 | 5 | 0.1 | 0.1 |
| 22 | 7 | 0.2 | 0.2 |
| 23 | 5 | 0.1 | 0.1 |
| 24 | 9 | 0.3 | 0.3 |
| 25 | 18 | 0.5 | 0.5 |
| 26 | 3 | 0.1 | 0.1 |
| 27 | 7 | 0.2 | 0.2 |
| 28 | 11 | 0.3 | 0.3 |
| 29 | 6 | 0.2 | 0.2 |
| 30 | 62 | 1.7 | 1.7 |
| 31 | 13 | 0.4 | 0.4 |
| 32 | 14 | 0.4 | 0.4 |
| 33 | 9 | 0.3 | 0.3 |
| 34 | 6 | 0.2 | 0.2 |
| 35 | 79 | 2.2 | 2.2 |
| 36 | 18 | 0.5 | 0.5 |
| 37 | 11 | 0.3 | 0.3 |
| 38 | 24 | 0.7 | 0.7 |
| 39 | 14 | 0.4 | 0.4 |
| 4 | 2 | 0.1 | 0.1 |
| 40 | 165 | 4.6 | 4.6 |
| 41 | 15 | 0.4 | 0.4 |
| 42 | 33 | 0.9 | 0.9 |
| 43 | 19 | 0.5 | 0.5 |
| 44 | 17 | 0.5 | 0.5 |
| 45 | 154 | 4.3 | 4.3 |
| 46 | 26 | 0.7 | 0.7 |
| 47 | 21 | 0.6 | 0.6 |
| 48 | 42 | 1.2 | 1.2 |
| 49 | 29 | 0.8 | 0.8 |
| 5 | 5 | 0.1 | 0.1 |
| 50 | 251 | 7.1 | 7.1 |
| 51 | 23 | 0.6 | 0.6 |
| 52 | 45 | 1.3 | 1.3 |
| 53 | 18 | 0.5 | 0.5 |
| 54 | 49 | 1.4 | 1.4 |
| 55 | 166 | 4.7 | 4.7 |
| 56 | 52 | 1.5 | 1.5 |
| 57 | 38 | 1.1 | 1.1 |
| 58 | 62 | 1.7 | 1.7 |
| 59 | 37 | 1.0 | 1.0 |
| 6 | 1 | 0.0 | 0.0 |
| 60 | 163 | 4.6 | 4.6 |
| 61 | 35 | 1.0 | 1.0 |
| 62 | 53 | 1.5 | 1.5 |
| 63 | 25 | 0.7 | 0.7 |
| 64 | 30 | 0.8 | 0.8 |
| 65 | 56 | 1.6 | 1.6 |
| 66 | 15 | 0.4 | 0.4 |
| 67 | 22 | 0.6 | 0.6 |
| 68 | 25 | 0.7 | 0.7 |
| 69 | 17 | 0.5 | 0.5 |
| 7 | 2 | 0.1 | 0.1 |
| 70 | 27 | 0.8 | 0.8 |
| 71 | 13 | 0.4 | 0.4 |
| 72 | 10 | 0.3 | 0.3 |
| 73 | 5 | 0.1 | 0.1 |
| 74 | 3 | 0.1 | 0.1 |
| 75 | 4 | 0.1 | 0.1 |
| 77 | 1 | 0.0 | 0.0 |
| 78 | 1 | 0.0 | 0.0 |
| 79 | 1 | 0.0 | 0.0 |
| 8 | 3 | 0.1 | 0.1 |
| 80 | 2 | 0.1 | 0.1 |
| 89 | 2 | 0.1 | 0.1 |
| 9 | 3 | 0.1 | 0.1 |
| 92 | 1 | 0.0 | 0.0 |
| 94 | 2 | 0.1 | 0.1 |
| 96 | 1 | 0.0 | 0.0 |
| 98 | 1 | 0.0 | 0.0 |
| 99 | 4 | 0.1 | 0.1 |
| “NA” | 1391 | 39.1 | 39.1 |
| Total | 3557 | 100.0 | 100.0 |
# Peripheral arterial disease
b4ea <- as.factor(d[,"b4ea"])
levels(b4ea) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ea <- ordered(b4ea, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ea)
new.d <- apply_labels(new.d, b4ea = "Peripheral arterial disease")
temp.d <- data.frame (new.d, b4ea)
result<-questionr::freq(temp.d$b4ea,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Peripheral arterial disease")
| n | % | val% | |
|---|---|---|---|
| No | 3031 | 85.2 | 93.3 |
| Yes | 215 | 6.0 | 6.6 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 309 | 8.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4eb <- as.factor(d[,"b4eb"])
new.d <- data.frame(new.d, b4eb)
new.d <- apply_labels(new.d, b4eb = "Peripheral arterial disease age")
temp.d <- data.frame (new.d, b4eb)
result<-questionr::freq(temp.d$b4eb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Peripheral arterial disease Age")
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.0 | 0.0 |
| ** | 1 | 0.0 | 0.0 |
| 0 | 23 | 0.6 | 0.6 |
| 1 | 1 | 0.0 | 0.0 |
| 16 | 1 | 0.0 | 0.0 |
| 17 | 1 | 0.0 | 0.0 |
| 19 | 1 | 0.0 | 0.0 |
| 25 | 1 | 0.0 | 0.0 |
| 26 | 1 | 0.0 | 0.0 |
| 30 | 2 | 0.1 | 0.1 |
| 31 | 1 | 0.0 | 0.0 |
| 33 | 1 | 0.0 | 0.0 |
| 34 | 2 | 0.1 | 0.1 |
| 35 | 4 | 0.1 | 0.1 |
| 36 | 1 | 0.0 | 0.0 |
| 37 | 1 | 0.0 | 0.0 |
| 40 | 12 | 0.3 | 0.3 |
| 41 | 1 | 0.0 | 0.0 |
| 42 | 1 | 0.0 | 0.0 |
| 44 | 2 | 0.1 | 0.1 |
| 45 | 5 | 0.1 | 0.1 |
| 46 | 1 | 0.0 | 0.0 |
| 47 | 1 | 0.0 | 0.0 |
| 48 | 7 | 0.2 | 0.2 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 19 | 0.5 | 0.5 |
| 51 | 4 | 0.1 | 0.1 |
| 52 | 1 | 0.0 | 0.0 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 6 | 0.2 | 0.2 |
| 55 | 13 | 0.4 | 0.4 |
| 56 | 5 | 0.1 | 0.1 |
| 57 | 6 | 0.2 | 0.2 |
| 58 | 12 | 0.3 | 0.3 |
| 59 | 5 | 0.1 | 0.1 |
| 60 | 22 | 0.6 | 0.6 |
| 61 | 2 | 0.1 | 0.1 |
| 62 | 11 | 0.3 | 0.3 |
| 63 | 3 | 0.1 | 0.1 |
| 64 | 7 | 0.2 | 0.2 |
| 65 | 15 | 0.4 | 0.4 |
| 66 | 5 | 0.1 | 0.1 |
| 67 | 5 | 0.1 | 0.1 |
| 68 | 7 | 0.2 | 0.2 |
| 69 | 6 | 0.2 | 0.2 |
| 70 | 9 | 0.3 | 0.3 |
| 71 | 2 | 0.1 | 0.1 |
| 72 | 3 | 0.1 | 0.1 |
| 73 | 3 | 0.1 | 0.1 |
| 74 | 3 | 0.1 | 0.1 |
| 76 | 1 | 0.0 | 0.0 |
| 77 | 1 | 0.0 | 0.0 |
| 78 | 2 | 0.1 | 0.1 |
| 82 | 1 | 0.0 | 0.0 |
| 84 | 1 | 0.0 | 0.0 |
| 94 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| “NA” | 3299 | 92.7 | 92.7 |
| Total | 3557 | 100.0 | 100.0 |
# High Cholesterol
b4fa <- as.factor(d[,"b4fa"])
levels(b4fa) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4fa <- ordered(b4fa, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4fa)
new.d <- apply_labels(new.d, b4fa = "High Cholesterol")
temp.d <- data.frame (new.d, b4fa)
result<-questionr::freq(temp.d$b4fa, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "High Cholesterol")
| n | % | val% | |
|---|---|---|---|
| No | 1502 | 42.2 | 45.1 |
| Yes | 1828 | 51.4 | 54.8 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 224 | 6.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4fb <- as.factor(d[,"b4fb"])
new.d <- data.frame(new.d, b4fb)
new.d <- apply_labels(new.d, b4fb = "High Cholesterol age")
temp.d <- data.frame (new.d, b4fb)
result<-questionr::freq(temp.d$b4fb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "High Cholesterol Age")
| n | % | val% | |
|---|---|---|---|
| 1 | 3 | 0.1 | 0.1 |
| 10 | 5 | 0.1 | 0.1 |
| 12 | 2 | 0.1 | 0.1 |
| 14 | 1 | 0.0 | 0.0 |
| 15 | 1 | 0.0 | 0.0 |
| 16 | 2 | 0.1 | 0.1 |
| 17 | 1 | 0.0 | 0.0 |
| 18 | 1 | 0.0 | 0.0 |
| 19 | 4 | 0.1 | 0.1 |
| 2 | 1 | 0.0 | 0.0 |
| 20 | 3 | 0.1 | 0.1 |
| 21 | 2 | 0.1 | 0.1 |
| 22 | 1 | 0.0 | 0.0 |
| 24 | 5 | 0.1 | 0.1 |
| 25 | 4 | 0.1 | 0.1 |
| 26 | 2 | 0.1 | 0.1 |
| 27 | 3 | 0.1 | 0.1 |
| 28 | 6 | 0.2 | 0.2 |
| 29 | 2 | 0.1 | 0.1 |
| 30 | 14 | 0.4 | 0.4 |
| 31 | 4 | 0.1 | 0.1 |
| 32 | 6 | 0.2 | 0.2 |
| 33 | 1 | 0.0 | 0.0 |
| 34 | 7 | 0.2 | 0.2 |
| 35 | 35 | 1.0 | 1.0 |
| 36 | 15 | 0.4 | 0.4 |
| 37 | 4 | 0.1 | 0.1 |
| 38 | 16 | 0.4 | 0.4 |
| 39 | 7 | 0.2 | 0.2 |
| 4 | 1 | 0.0 | 0.0 |
| 40 | 74 | 2.1 | 2.1 |
| 41 | 8 | 0.2 | 0.2 |
| 42 | 14 | 0.4 | 0.4 |
| 43 | 9 | 0.3 | 0.3 |
| 44 | 11 | 0.3 | 0.3 |
| 45 | 86 | 2.4 | 2.4 |
| 46 | 14 | 0.4 | 0.4 |
| 47 | 13 | 0.4 | 0.4 |
| 48 | 29 | 0.8 | 0.8 |
| 49 | 12 | 0.3 | 0.3 |
| 5 | 5 | 0.1 | 0.1 |
| 50 | 174 | 4.9 | 4.9 |
| 51 | 19 | 0.5 | 0.5 |
| 52 | 29 | 0.8 | 0.8 |
| 53 | 19 | 0.5 | 0.5 |
| 54 | 37 | 1.0 | 1.0 |
| 55 | 134 | 3.8 | 3.8 |
| 56 | 37 | 1.0 | 1.0 |
| 57 | 42 | 1.2 | 1.2 |
| 58 | 39 | 1.1 | 1.1 |
| 59 | 32 | 0.9 | 0.9 |
| 6 | 2 | 0.1 | 0.1 |
| 60 | 138 | 3.9 | 3.9 |
| 61 | 24 | 0.7 | 0.7 |
| 62 | 57 | 1.6 | 1.6 |
| 63 | 29 | 0.8 | 0.8 |
| 64 | 25 | 0.7 | 0.7 |
| 65 | 53 | 1.5 | 1.5 |
| 66 | 13 | 0.4 | 0.4 |
| 67 | 16 | 0.4 | 0.4 |
| 68 | 23 | 0.6 | 0.6 |
| 69 | 25 | 0.7 | 0.7 |
| 7 | 2 | 0.1 | 0.1 |
| 70 | 31 | 0.9 | 0.9 |
| 71 | 6 | 0.2 | 0.2 |
| 72 | 13 | 0.4 | 0.4 |
| 73 | 6 | 0.2 | 0.2 |
| 74 | 9 | 0.3 | 0.3 |
| 75 | 8 | 0.2 | 0.2 |
| 76 | 3 | 0.1 | 0.1 |
| 77 | 1 | 0.0 | 0.0 |
| 8 | 1 | 0.0 | 0.0 |
| 80 | 1 | 0.0 | 0.0 |
| 86 | 1 | 0.0 | 0.0 |
| 9 | 1 | 0.0 | 0.0 |
| 92 | 1 | 0.0 | 0.0 |
| 94 | 1 | 0.0 | 0.0 |
| 95 | 1 | 0.0 | 0.0 |
| 96 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| 99 | 2 | 0.1 | 0.1 |
| “NA” | 2066 | 58.1 | 58.1 |
| Total | 3557 | 100.0 | 100.0 |
# Asthma, COPD
b4ga <- as.factor(d[,"b4ga"])
levels(b4ga) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ga <- ordered(b4ga, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ga)
new.d <- apply_labels(new.d, b4ga = "Asthma, COPD")
temp.d <- data.frame (new.d, b4ga)
result<-questionr::freq(temp.d$b4ga, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Asthma, COPD")
| n | % | val% | |
|---|---|---|---|
| No | 2927 | 82.3 | 84.6 |
| Yes | 529 | 14.9 | 15.3 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 99 | 2.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4gb <- as.factor(d[,"b4gb"])
new.d <- data.frame(new.d, b4gb)
new.d <- apply_labels(new.d, b4gb = "Asthma, COPD age")
temp.d <- data.frame (new.d, b4gb)
result<-questionr::freq(temp.d$b4gb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Asthma, COPD Age")
| n | % | val% | |
|---|---|---|---|
| 06 | 2 | 0.1 | 0.1 |
| 1 | 10 | 0.3 | 0.3 |
| 10 | 19 | 0.5 | 0.5 |
| 11 | 4 | 0.1 | 0.1 |
| 12 | 11 | 0.3 | 0.3 |
| 13 | 2 | 0.1 | 0.1 |
| 14 | 5 | 0.1 | 0.1 |
| 15 | 4 | 0.1 | 0.1 |
| 16 | 3 | 0.1 | 0.1 |
| 17 | 2 | 0.1 | 0.1 |
| 18 | 9 | 0.3 | 0.3 |
| 19 | 3 | 0.1 | 0.1 |
| 2 | 6 | 0.2 | 0.2 |
| 20 | 6 | 0.2 | 0.2 |
| 21 | 2 | 0.1 | 0.1 |
| 23 | 1 | 0.0 | 0.0 |
| 25 | 6 | 0.2 | 0.2 |
| 26 | 1 | 0.0 | 0.0 |
| 27 | 3 | 0.1 | 0.1 |
| 28 | 2 | 0.1 | 0.1 |
| 29 | 1 | 0.0 | 0.0 |
| 3 | 2 | 0.1 | 0.1 |
| 30 | 8 | 0.2 | 0.2 |
| 31 | 1 | 0.0 | 0.0 |
| 32 | 3 | 0.1 | 0.1 |
| 33 | 2 | 0.1 | 0.1 |
| 35 | 4 | 0.1 | 0.1 |
| 37 | 1 | 0.0 | 0.0 |
| 38 | 3 | 0.1 | 0.1 |
| 39 | 1 | 0.0 | 0.0 |
| 4 | 10 | 0.3 | 0.3 |
| 40 | 10 | 0.3 | 0.3 |
| 42 | 4 | 0.1 | 0.1 |
| 43 | 1 | 0.0 | 0.0 |
| 45 | 9 | 0.3 | 0.3 |
| 46 | 1 | 0.0 | 0.0 |
| 47 | 1 | 0.0 | 0.0 |
| 48 | 4 | 0.1 | 0.1 |
| 49 | 2 | 0.1 | 0.1 |
| 5 | 28 | 0.8 | 0.8 |
| 50 | 24 | 0.7 | 0.7 |
| 51 | 4 | 0.1 | 0.1 |
| 52 | 6 | 0.2 | 0.2 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 3 | 0.1 | 0.1 |
| 55 | 16 | 0.4 | 0.4 |
| 56 | 12 | 0.3 | 0.3 |
| 57 | 13 | 0.4 | 0.4 |
| 58 | 9 | 0.3 | 0.3 |
| 59 | 10 | 0.3 | 0.3 |
| 6 | 14 | 0.4 | 0.4 |
| 60 | 28 | 0.8 | 0.8 |
| 61 | 2 | 0.1 | 0.1 |
| 62 | 11 | 0.3 | 0.3 |
| 63 | 11 | 0.3 | 0.3 |
| 64 | 6 | 0.2 | 0.2 |
| 65 | 16 | 0.4 | 0.4 |
| 66 | 5 | 0.1 | 0.1 |
| 67 | 7 | 0.2 | 0.2 |
| 68 | 7 | 0.2 | 0.2 |
| 69 | 6 | 0.2 | 0.2 |
| 7 | 12 | 0.3 | 0.3 |
| 70 | 9 | 0.3 | 0.3 |
| 71 | 6 | 0.2 | 0.2 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 4 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 4 | 0.1 | 0.1 |
| 77 | 3 | 0.1 | 0.1 |
| 78 | 2 | 0.1 | 0.1 |
| 79 | 1 | 0.0 | 0.0 |
| 8 | 8 | 0.2 | 0.2 |
| 80 | 1 | 0.0 | 0.0 |
| 81 | 1 | 0.0 | 0.0 |
| 9 | 8 | 0.2 | 0.2 |
| 93 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| “NA” | 3083 | 86.7 | 86.7 |
| Total | 3557 | 100.0 | 100.0 |
# Stomach ulcers
b4ha <- as.factor(d[,"b4ha"])
levels(b4ha) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ha <- ordered(b4ha, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ha)
new.d <- apply_labels(new.d, b4ha = "Stomach ulcers")
temp.d <- data.frame (new.d, b4ha)
result<-questionr::freq(temp.d$b4ha, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Stomach ulcers")
| n | % | val% | |
|---|---|---|---|
| No | 3142 | 88.3 | 91.4 |
| Yes | 294 | 8.3 | 8.6 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 120 | 3.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4hb <- as.factor(d[,"b4hb"])
new.d <- data.frame(new.d, b4hb)
new.d <- apply_labels(new.d, b4hb = "Stomach ulcers age")
temp.d <- data.frame (new.d, b4hb)
result<-questionr::freq(temp.d$b4hb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Stomach ulcers Age")
| n | % | val% | |
|---|---|---|---|
| 0 | 46 | 1.3 | 1.3 |
| 10 | 2 | 0.1 | 0.1 |
| 13 | 2 | 0.1 | 0.1 |
| 14 | 3 | 0.1 | 0.1 |
| 15 | 3 | 0.1 | 0.1 |
| 16 | 4 | 0.1 | 0.1 |
| 17 | 1 | 0.0 | 0.0 |
| 18 | 4 | 0.1 | 0.1 |
| 19 | 3 | 0.1 | 0.1 |
| 2 | 1 | 0.0 | 0.0 |
| 20 | 4 | 0.1 | 0.1 |
| 21 | 1 | 0.0 | 0.0 |
| 22 | 7 | 0.2 | 0.2 |
| 23 | 3 | 0.1 | 0.1 |
| 24 | 4 | 0.1 | 0.1 |
| 25 | 9 | 0.3 | 0.3 |
| 27 | 3 | 0.1 | 0.1 |
| 28 | 4 | 0.1 | 0.1 |
| 3 | 1 | 0.0 | 0.0 |
| 30 | 12 | 0.3 | 0.3 |
| 32 | 3 | 0.1 | 0.1 |
| 34 | 3 | 0.1 | 0.1 |
| 35 | 17 | 0.5 | 0.5 |
| 36 | 4 | 0.1 | 0.1 |
| 38 | 1 | 0.0 | 0.0 |
| 39 | 3 | 0.1 | 0.1 |
| 40 | 14 | 0.4 | 0.4 |
| 42 | 3 | 0.1 | 0.1 |
| 44 | 2 | 0.1 | 0.1 |
| 45 | 15 | 0.4 | 0.4 |
| 46 | 2 | 0.1 | 0.1 |
| 47 | 3 | 0.1 | 0.1 |
| 48 | 6 | 0.2 | 0.2 |
| 49 | 1 | 0.0 | 0.0 |
| 50 | 14 | 0.4 | 0.4 |
| 52 | 2 | 0.1 | 0.1 |
| 53 | 1 | 0.0 | 0.0 |
| 54 | 1 | 0.0 | 0.0 |
| 55 | 5 | 0.1 | 0.1 |
| 56 | 2 | 0.1 | 0.1 |
| 57 | 4 | 0.1 | 0.1 |
| 58 | 4 | 0.1 | 0.1 |
| 59 | 3 | 0.1 | 0.1 |
| 60 | 11 | 0.3 | 0.3 |
| 61 | 1 | 0.0 | 0.0 |
| 62 | 9 | 0.3 | 0.3 |
| 63 | 5 | 0.1 | 0.1 |
| 64 | 3 | 0.1 | 0.1 |
| 65 | 7 | 0.2 | 0.2 |
| 66 | 3 | 0.1 | 0.1 |
| 67 | 5 | 0.1 | 0.1 |
| 68 | 3 | 0.1 | 0.1 |
| 69 | 2 | 0.1 | 0.1 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 2 | 0.1 | 0.1 |
| 71 | 1 | 0.0 | 0.0 |
| 72 | 3 | 0.1 | 0.1 |
| 73 | 1 | 0.0 | 0.0 |
| 74 | 1 | 0.0 | 0.0 |
| 76 | 1 | 0.0 | 0.0 |
| 8 | 1 | 0.0 | 0.0 |
| 80 | 1 | 0.0 | 0.0 |
| 9 | 2 | 0.1 | 0.1 |
| 94 | 1 | 0.0 | 0.0 |
| “NA” | 3263 | 91.7 | 91.7 |
| Total | 3557 | 100.0 | 100.0 |
# Crohn's Disease
b4ia <- as.factor(d[,"b4ia"])
levels(b4ia) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ia <- ordered(b4ia, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4ia)
new.d <- apply_labels(new.d, b4ia = "Crohn's Disease")
temp.d <- data.frame (new.d, b4ia)
result<-questionr::freq(temp.d$b4ia, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Crohn's Disease")
| n | % | val% | |
|---|---|---|---|
| No | 3314 | 93.2 | 96.7 |
| Yes | 114 | 3.2 | 3.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 129 | 3.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4ib <- as.factor(d[,"b4ib"])
new.d <- data.frame(new.d, b4ib)
new.d <- apply_labels(new.d, b4ib = "Crohn's Disease age")
temp.d <- data.frame (new.d, b4ib)
result<-questionr::freq(temp.d$b4ib, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Crohn's Disease Age")
| n | % | val% | |
|---|---|---|---|
| 15 | 1 | 0.0 | 0.0 |
| 2 | 2 | 0.1 | 0.1 |
| 22 | 2 | 0.1 | 0.1 |
| 30 | 1 | 0.0 | 0.0 |
| 32 | 3 | 0.1 | 0.1 |
| 33 | 1 | 0.0 | 0.0 |
| 34 | 1 | 0.0 | 0.0 |
| 35 | 2 | 0.1 | 0.1 |
| 37 | 1 | 0.0 | 0.0 |
| 39 | 1 | 0.0 | 0.0 |
| 40 | 11 | 0.3 | 0.3 |
| 41 | 1 | 0.0 | 0.0 |
| 44 | 5 | 0.1 | 0.1 |
| 45 | 2 | 0.1 | 0.1 |
| 46 | 1 | 0.0 | 0.0 |
| 48 | 2 | 0.1 | 0.1 |
| 50 | 8 | 0.2 | 0.2 |
| 51 | 3 | 0.1 | 0.1 |
| 52 | 3 | 0.1 | 0.1 |
| 53 | 1 | 0.0 | 0.0 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 8 | 0.2 | 0.2 |
| 56 | 2 | 0.1 | 0.1 |
| 57 | 1 | 0.0 | 0.0 |
| 58 | 5 | 0.1 | 0.1 |
| 59 | 1 | 0.0 | 0.0 |
| 60 | 6 | 0.2 | 0.2 |
| 62 | 1 | 0.0 | 0.0 |
| 63 | 2 | 0.1 | 0.1 |
| 64 | 1 | 0.0 | 0.0 |
| 65 | 3 | 0.1 | 0.1 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 1 | 0.0 | 0.0 |
| 69 | 3 | 0.1 | 0.1 |
| 70 | 2 | 0.1 | 0.1 |
| 71 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.0 | 0.0 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 2 | 0.1 | 0.1 |
| 79 | 1 | 0.0 | 0.0 |
| 85 | 1 | 0.0 | 0.0 |
| “NA” | 3456 | 97.2 | 97.2 |
| Total | 3557 | 100.0 | 100.0 |
# Diabetes
b4ja <- as.factor(d[,"b4ja"])
levels(b4ja) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ja <- ordered(b4ja, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4ja)
new.d <- apply_labels(new.d, b4ja = "Diabetes")
temp.d <- data.frame (new.d, b4ja)
result<-questionr::freq(temp.d$b4ja, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Diabetes")
| n | % | val% | |
|---|---|---|---|
| No | 2383 | 67.0 | 68.6 |
| Yes | 1086 | 30.5 | 31.3 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 84 | 2.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4jb <- as.factor(d[,"b4jb"])
new.d <- data.frame(new.d, b4jb)
new.d <- apply_labels(new.d, b4jb = "Diabetes age")
temp.d <- data.frame (new.d, b4jb)
result<-questionr::freq(temp.d$b4jb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Diabetes Age")
| n | % | val% | |
|---|---|---|---|
| 0 | 10 | 0.3 | 0.3 |
| 10 | 1 | 0.0 | 0.0 |
| 12 | 2 | 0.1 | 0.1 |
| 13 | 2 | 0.1 | 0.1 |
| 14 | 2 | 0.1 | 0.1 |
| 15 | 2 | 0.1 | 0.1 |
| 16 | 1 | 0.0 | 0.0 |
| 17 | 4 | 0.1 | 0.1 |
| 18 | 1 | 0.0 | 0.0 |
| 19 | 1 | 0.0 | 0.0 |
| 2 | 1 | 0.0 | 0.0 |
| 20 | 3 | 0.1 | 0.1 |
| 22 | 1 | 0.0 | 0.0 |
| 24 | 2 | 0.1 | 0.1 |
| 27 | 1 | 0.0 | 0.0 |
| 28 | 2 | 0.1 | 0.1 |
| 29 | 5 | 0.1 | 0.1 |
| 3 | 2 | 0.1 | 0.1 |
| 30 | 14 | 0.4 | 0.4 |
| 31 | 1 | 0.0 | 0.0 |
| 32 | 1 | 0.0 | 0.0 |
| 34 | 1 | 0.0 | 0.0 |
| 35 | 21 | 0.6 | 0.6 |
| 36 | 3 | 0.1 | 0.1 |
| 37 | 5 | 0.1 | 0.1 |
| 38 | 7 | 0.2 | 0.2 |
| 39 | 6 | 0.2 | 0.2 |
| 40 | 37 | 1.0 | 1.0 |
| 41 | 4 | 0.1 | 0.1 |
| 42 | 13 | 0.4 | 0.4 |
| 43 | 12 | 0.3 | 0.3 |
| 44 | 8 | 0.2 | 0.2 |
| 45 | 49 | 1.4 | 1.4 |
| 46 | 8 | 0.2 | 0.2 |
| 47 | 12 | 0.3 | 0.3 |
| 48 | 17 | 0.5 | 0.5 |
| 49 | 8 | 0.2 | 0.2 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 79 | 2.2 | 2.2 |
| 51 | 13 | 0.4 | 0.4 |
| 52 | 16 | 0.4 | 0.4 |
| 53 | 20 | 0.6 | 0.6 |
| 54 | 28 | 0.8 | 0.8 |
| 55 | 78 | 2.2 | 2.2 |
| 56 | 28 | 0.8 | 0.8 |
| 57 | 22 | 0.6 | 0.6 |
| 58 | 39 | 1.1 | 1.1 |
| 59 | 28 | 0.8 | 0.8 |
| 60 | 75 | 2.1 | 2.1 |
| 61 | 29 | 0.8 | 0.8 |
| 62 | 37 | 1.0 | 1.0 |
| 63 | 17 | 0.5 | 0.5 |
| 64 | 21 | 0.6 | 0.6 |
| 65 | 40 | 1.1 | 1.1 |
| 66 | 14 | 0.4 | 0.4 |
| 67 | 5 | 0.1 | 0.1 |
| 68 | 13 | 0.4 | 0.4 |
| 69 | 16 | 0.4 | 0.4 |
| 70 | 24 | 0.7 | 0.7 |
| 71 | 6 | 0.2 | 0.2 |
| 72 | 4 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 3 | 0.1 | 0.1 |
| 75 | 5 | 0.1 | 0.1 |
| 76 | 2 | 0.1 | 0.1 |
| 78 | 1 | 0.0 | 0.0 |
| 81 | 1 | 0.0 | 0.0 |
| 94 | 1 | 0.0 | 0.0 |
| 95 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| “NA” | 2617 | 73.6 | 73.6 |
| Total | 3557 | 100.0 | 100.0 |
# Kidney Problems
b4ka <- as.factor(d[,"b4ka"])
levels(b4ka) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ka <- ordered(b4ka, c("No", "Yes", "Scantron_Error"))
new.d <- data.frame(new.d, b4ka)
new.d <- apply_labels(new.d, b4ka = "Kidney Problems")
temp.d <- data.frame (new.d, b4ka)
result<-questionr::freq(temp.d$b4ka, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Kidney Problems")
| n | % | val% | |
|---|---|---|---|
| No | 3253 | 91.5 | 94.0 |
| Yes | 206 | 5.8 | 6.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 96 | 2.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4kb <- as.factor(d[,"b4kb"])
new.d <- data.frame(new.d, b4kb)
new.d <- apply_labels(new.d, b4kb = "Kidney Problems age")
temp.d <- data.frame (new.d, b4kb)
result<-questionr::freq(temp.d$b4kb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Kidney Problems Age")
| n | % | val% | |
|---|---|---|---|
| 11 | 1 | 0.0 | 0.0 |
| 15 | 3 | 0.1 | 0.1 |
| 16 | 1 | 0.0 | 0.0 |
| 17 | 1 | 0.0 | 0.0 |
| 29 | 1 | 0.0 | 0.0 |
| 35 | 2 | 0.1 | 0.1 |
| 38 | 1 | 0.0 | 0.0 |
| 40 | 5 | 0.1 | 0.1 |
| 42 | 1 | 0.0 | 0.0 |
| 44 | 1 | 0.0 | 0.0 |
| 45 | 3 | 0.1 | 0.1 |
| 46 | 1 | 0.0 | 0.0 |
| 47 | 1 | 0.0 | 0.0 |
| 48 | 1 | 0.0 | 0.0 |
| 49 | 1 | 0.0 | 0.0 |
| 5 | 2 | 0.1 | 0.1 |
| 50 | 11 | 0.3 | 0.3 |
| 51 | 3 | 0.1 | 0.1 |
| 52 | 2 | 0.1 | 0.1 |
| 53 | 4 | 0.1 | 0.1 |
| 54 | 5 | 0.1 | 0.1 |
| 55 | 11 | 0.3 | 0.3 |
| 56 | 6 | 0.2 | 0.2 |
| 57 | 4 | 0.1 | 0.1 |
| 58 | 4 | 0.1 | 0.1 |
| 59 | 5 | 0.1 | 0.1 |
| 60 | 6 | 0.2 | 0.2 |
| 61 | 5 | 0.1 | 0.1 |
| 62 | 8 | 0.2 | 0.2 |
| 63 | 1 | 0.0 | 0.0 |
| 64 | 5 | 0.1 | 0.1 |
| 65 | 11 | 0.3 | 0.3 |
| 66 | 4 | 0.1 | 0.1 |
| 67 | 6 | 0.2 | 0.2 |
| 68 | 6 | 0.2 | 0.2 |
| 69 | 5 | 0.1 | 0.1 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 7 | 0.2 | 0.2 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 3 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 4 | 0.1 | 0.1 |
| 76 | 1 | 0.0 | 0.0 |
| 77 | 2 | 0.1 | 0.1 |
| 80 | 1 | 0.0 | 0.0 |
| 83 | 1 | 0.0 | 0.0 |
| 95 | 1 | 0.0 | 0.0 |
| “NA” | 3393 | 95.4 | 95.4 |
| Total | 3557 | 100.0 | 100.0 |
# Cirrhosis, liver damage
b4la <- as.factor(d[,"b4la"])
levels(b4la) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4la <- ordered(b4la, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4la)
new.d <- apply_labels(new.d, b4la = "Cirrhosis, liver damage")
temp.d <- data.frame (new.d, b4la)
result<-questionr::freq(temp.d$b4la, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Cirrhosis, liver damage")
| n | % | val% | |
|---|---|---|---|
| No | 3376 | 94.9 | 97.9 |
| Yes | 71 | 2.0 | 2.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 110 | 3.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4lb <- as.factor(d[,"b4lb"])
new.d <- data.frame(new.d, b4lb)
new.d <- apply_labels(new.d, b4lb = "Cirrhosis, liver damage age")
temp.d <- data.frame (new.d, b4lb)
result<-questionr::freq(temp.d$b4lb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Cirrhosis, liver damage Age")
| n | % | val% | |
|---|---|---|---|
| 18 | 1 | 0.0 | 0.0 |
| 21 | 1 | 0.0 | 0.0 |
| 39 | 1 | 0.0 | 0.0 |
| 40 | 1 | 0.0 | 0.0 |
| 42 | 1 | 0.0 | 0.0 |
| 45 | 5 | 0.1 | 0.1 |
| 47 | 1 | 0.0 | 0.0 |
| 48 | 2 | 0.1 | 0.1 |
| 49 | 1 | 0.0 | 0.0 |
| 50 | 2 | 0.1 | 0.1 |
| 51 | 2 | 0.1 | 0.1 |
| 53 | 1 | 0.0 | 0.0 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 3 | 0.1 | 0.1 |
| 58 | 1 | 0.0 | 0.0 |
| 60 | 8 | 0.2 | 0.2 |
| 61 | 1 | 0.0 | 0.0 |
| 63 | 1 | 0.0 | 0.0 |
| 64 | 1 | 0.0 | 0.0 |
| 65 | 3 | 0.1 | 0.1 |
| 66 | 3 | 0.1 | 0.1 |
| 67 | 2 | 0.1 | 0.1 |
| 68 | 2 | 0.1 | 0.1 |
| 69 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.0 | 0.0 |
| 77 | 1 | 0.0 | 0.0 |
| “NA” | 3507 | 98.6 | 98.6 |
| Total | 3557 | 100.0 | 100.0 |
# Arthritis
b4ma <- as.factor(d[,"b4ma"])
levels(b4ma) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4ma <- ordered(b4ma, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4ma)
new.d <- apply_labels(new.d, b4ma = "Arthritis")
temp.d <- data.frame (new.d, b4ma)
result<-questionr::freq(temp.d$b4ma, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Arthritis")
| n | % | val% | |
|---|---|---|---|
| No | 3006 | 84.5 | 87.3 |
| Yes | 436 | 12.3 | 12.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 113 | 3.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4mb <- as.factor(d[,"b4mb"])
new.d <- data.frame(new.d, b4mb)
new.d <- apply_labels(new.d, b4mb = "Arthritis age")
temp.d <- data.frame (new.d, b4mb)
result<-questionr::freq(temp.d$b4mb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Arthritis Age")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.0 | 0.0 |
| 10 | 1 | 0.0 | 0.0 |
| 17 | 1 | 0.0 | 0.0 |
| 19 | 1 | 0.0 | 0.0 |
| 2 | 1 | 0.0 | 0.0 |
| 20 | 2 | 0.1 | 0.1 |
| 21 | 1 | 0.0 | 0.0 |
| 22 | 1 | 0.0 | 0.0 |
| 23 | 1 | 0.0 | 0.0 |
| 24 | 1 | 0.0 | 0.0 |
| 25 | 3 | 0.1 | 0.1 |
| 28 | 1 | 0.0 | 0.0 |
| 30 | 9 | 0.3 | 0.3 |
| 32 | 2 | 0.1 | 0.1 |
| 33 | 1 | 0.0 | 0.0 |
| 35 | 7 | 0.2 | 0.2 |
| 36 | 2 | 0.1 | 0.1 |
| 38 | 2 | 0.1 | 0.1 |
| 39 | 3 | 0.1 | 0.1 |
| 4 | 2 | 0.1 | 0.1 |
| 40 | 19 | 0.5 | 0.5 |
| 41 | 5 | 0.1 | 0.1 |
| 42 | 4 | 0.1 | 0.1 |
| 43 | 4 | 0.1 | 0.1 |
| 44 | 4 | 0.1 | 0.1 |
| 45 | 17 | 0.5 | 0.5 |
| 46 | 2 | 0.1 | 0.1 |
| 47 | 4 | 0.1 | 0.1 |
| 48 | 7 | 0.2 | 0.2 |
| 49 | 2 | 0.1 | 0.1 |
| 50 | 37 | 1.0 | 1.0 |
| 51 | 7 | 0.2 | 0.2 |
| 52 | 8 | 0.2 | 0.2 |
| 53 | 6 | 0.2 | 0.2 |
| 54 | 9 | 0.3 | 0.3 |
| 55 | 32 | 0.9 | 0.9 |
| 56 | 7 | 0.2 | 0.2 |
| 57 | 7 | 0.2 | 0.2 |
| 58 | 14 | 0.4 | 0.4 |
| 59 | 2 | 0.1 | 0.1 |
| 60 | 34 | 1.0 | 1.0 |
| 61 | 5 | 0.1 | 0.1 |
| 62 | 10 | 0.3 | 0.3 |
| 63 | 8 | 0.2 | 0.2 |
| 64 | 9 | 0.3 | 0.3 |
| 65 | 16 | 0.4 | 0.4 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 6 | 0.2 | 0.2 |
| 68 | 7 | 0.2 | 0.2 |
| 69 | 5 | 0.1 | 0.1 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 6 | 0.2 | 0.2 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 5 | 0.1 | 0.1 |
| 73 | 1 | 0.0 | 0.0 |
| 74 | 1 | 0.0 | 0.0 |
| 75 | 3 | 0.1 | 0.1 |
| 76 | 1 | 0.0 | 0.0 |
| 77 | 1 | 0.0 | 0.0 |
| 80 | 1 | 0.0 | 0.0 |
| “NA” | 3192 | 89.7 | 89.7 |
| Total | 3557 | 100.0 | 100.0 |
# Dementia
b4na <- as.factor(d[,"b4na"])
levels(b4na) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4na <- ordered(b4na, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4na)
new.d <- apply_labels(new.d, b4na = "Dementia")
temp.d <- data.frame (new.d, b4na)
result<-questionr::freq(temp.d$b4na, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Dementia")
| n | % | val% | |
|---|---|---|---|
| No | 3420 | 96.1 | 98.7 |
| Yes | 45 | 1.3 | 1.3 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 91 | 2.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4nb <- as.factor(d[,"b4nb"])
new.d <- data.frame(new.d, b4nb)
new.d <- apply_labels(new.d, b4nb = "Dementia age")
temp.d <- data.frame (new.d, b4nb)
result<-questionr::freq(temp.d$b4nb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Dementia Age")
| n | % | val% | |
|---|---|---|---|
| 10 | 1 | 0.0 | 0.0 |
| 29 | 1 | 0.0 | 0.0 |
| 53 | 1 | 0.0 | 0.0 |
| 57 | 1 | 0.0 | 0.0 |
| 60 | 1 | 0.0 | 0.0 |
| 62 | 2 | 0.1 | 0.1 |
| 63 | 1 | 0.0 | 0.0 |
| 64 | 1 | 0.0 | 0.0 |
| 65 | 2 | 0.1 | 0.1 |
| 66 | 1 | 0.0 | 0.0 |
| 67 | 1 | 0.0 | 0.0 |
| 69 | 1 | 0.0 | 0.0 |
| 70 | 6 | 0.2 | 0.2 |
| 72 | 3 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.0 | 0.0 |
| 75 | 1 | 0.0 | 0.0 |
| 80 | 1 | 0.0 | 0.0 |
| “NA” | 3529 | 99.2 | 99.2 |
| Total | 3557 | 100.0 | 100.0 |
# Depression
b4oa <- as.factor(d[,"b4oa"])
levels(b4oa) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4oa <- ordered(b4oa, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4oa)
new.d <- apply_labels(new.d, b4oa = "Depression")
temp.d <- data.frame (new.d, b4oa)
result<-questionr::freq(temp.d$b4oa, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Depression")
| n | % | val% | |
|---|---|---|---|
| No | 2992 | 84.1 | 87.0 |
| Yes | 447 | 12.6 | 13.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 116 | 3.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4ob <- as.factor(d[,"b4ob"])
new.d <- data.frame(new.d, b4ob)
new.d <- apply_labels(new.d, b4ob = "Depression age")
temp.d <- data.frame (new.d, b4ob)
result<-questionr::freq(temp.d$b4ob, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Depression Age")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.0 | 0.0 |
| 14 | 1 | 0.0 | 0.0 |
| 16 | 1 | 0.0 | 0.0 |
| 17 | 1 | 0.0 | 0.0 |
| 18 | 1 | 0.0 | 0.0 |
| 19 | 6 | 0.2 | 0.2 |
| 20 | 6 | 0.2 | 0.2 |
| 21 | 5 | 0.1 | 0.1 |
| 22 | 1 | 0.0 | 0.0 |
| 24 | 1 | 0.0 | 0.0 |
| 25 | 4 | 0.1 | 0.1 |
| 26 | 3 | 0.1 | 0.1 |
| 28 | 6 | 0.2 | 0.2 |
| 29 | 2 | 0.1 | 0.1 |
| 30 | 5 | 0.1 | 0.1 |
| 32 | 4 | 0.1 | 0.1 |
| 33 | 1 | 0.0 | 0.0 |
| 34 | 1 | 0.0 | 0.0 |
| 35 | 10 | 0.3 | 0.3 |
| 36 | 4 | 0.1 | 0.1 |
| 37 | 4 | 0.1 | 0.1 |
| 38 | 3 | 0.1 | 0.1 |
| 39 | 1 | 0.0 | 0.0 |
| 4 | 1 | 0.0 | 0.0 |
| 40 | 15 | 0.4 | 0.4 |
| 41 | 2 | 0.1 | 0.1 |
| 42 | 8 | 0.2 | 0.2 |
| 43 | 5 | 0.1 | 0.1 |
| 44 | 3 | 0.1 | 0.1 |
| 45 | 12 | 0.3 | 0.3 |
| 46 | 3 | 0.1 | 0.1 |
| 47 | 7 | 0.2 | 0.2 |
| 48 | 7 | 0.2 | 0.2 |
| 49 | 6 | 0.2 | 0.2 |
| 50 | 27 | 0.8 | 0.8 |
| 51 | 3 | 0.1 | 0.1 |
| 52 | 9 | 0.3 | 0.3 |
| 53 | 6 | 0.2 | 0.2 |
| 54 | 5 | 0.1 | 0.1 |
| 55 | 22 | 0.6 | 0.6 |
| 56 | 7 | 0.2 | 0.2 |
| 57 | 6 | 0.2 | 0.2 |
| 58 | 9 | 0.3 | 0.3 |
| 59 | 7 | 0.2 | 0.2 |
| 6 | 1 | 0.0 | 0.0 |
| 60 | 17 | 0.5 | 0.5 |
| 61 | 10 | 0.3 | 0.3 |
| 62 | 6 | 0.2 | 0.2 |
| 63 | 5 | 0.1 | 0.1 |
| 64 | 6 | 0.2 | 0.2 |
| 65 | 15 | 0.4 | 0.4 |
| 66 | 6 | 0.2 | 0.2 |
| 67 | 4 | 0.1 | 0.1 |
| 68 | 8 | 0.2 | 0.2 |
| 69 | 1 | 0.0 | 0.0 |
| 7 | 2 | 0.1 | 0.1 |
| 70 | 9 | 0.3 | 0.3 |
| 72 | 3 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 1 | 0.0 | 0.0 |
| 76 | 1 | 0.0 | 0.0 |
| 8 | 1 | 0.0 | 0.0 |
| 91 | 1 | 0.0 | 0.0 |
| 96 | 1 | 0.0 | 0.0 |
| 98 | 2 | 0.1 | 0.1 |
| “NA” | 3211 | 90.3 | 90.3 |
| Total | 3557 | 100.0 | 100.0 |
# AIDS
b4pa <- as.factor(d[,"b4pa"])
levels(b4pa) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4pa <- ordered(b4pa, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4pa)
new.d <- apply_labels(new.d, b4pa = "AIDS")
temp.d <- data.frame (new.d, b4pa)
result<-questionr::freq(temp.d$b4pa, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "AIDS")
| n | % | val% | |
|---|---|---|---|
| No | 3408 | 95.8 | 98.8 |
| Yes | 41 | 1.2 | 1.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 108 | 3.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4pb <- as.factor(d[,"b4pb"])
new.d <- data.frame(new.d, b4pb)
new.d <- apply_labels(new.d, b4pb = "AIDS age")
temp.d <- data.frame (new.d, b4pb)
result<-questionr::freq(temp.d$b4pb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "AIDS Age")
| n | % | val% | |
|---|---|---|---|
| 0 | 47 | 1.3 | 1.3 |
| 25 | 1 | 0.0 | 0.0 |
| 30 | 1 | 0.0 | 0.0 |
| 33 | 1 | 0.0 | 0.0 |
| 36 | 2 | 0.1 | 0.1 |
| 38 | 1 | 0.0 | 0.0 |
| 39 | 1 | 0.0 | 0.0 |
| 40 | 3 | 0.1 | 0.1 |
| 45 | 1 | 0.0 | 0.0 |
| 48 | 1 | 0.0 | 0.0 |
| 49 | 2 | 0.1 | 0.1 |
| 50 | 2 | 0.1 | 0.1 |
| 51 | 1 | 0.0 | 0.0 |
| 55 | 1 | 0.0 | 0.0 |
| 59 | 2 | 0.1 | 0.1 |
| 60 | 1 | 0.0 | 0.0 |
| 63 | 1 | 0.0 | 0.0 |
| 65 | 1 | 0.0 | 0.0 |
| 9 | 1 | 0.0 | 0.0 |
| 90 | 1 | 0.0 | 0.0 |
| “NA” | 3485 | 98.0 | 98.0 |
| Total | 3557 | 100.0 | 100.0 |
# Other Cancer
b4qa <- as.factor(d[,"b4qa"])
levels(b4qa) <- list(No="1",
Yes="2",
Scantron_Error="*")
b4qa <- ordered(b4qa, c("No", "Yes","Scantron_Error"))
new.d <- data.frame(new.d, b4qa)
new.d <- apply_labels(new.d, b4qa = "Other Cancer")
temp.d <- data.frame (new.d, b4qa)
result<-questionr::freq(temp.d$b4qa, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Other Cancer")
| n | % | val% | |
|---|---|---|---|
| No | 3172 | 89.2 | 93.3 |
| Yes | 228 | 6.4 | 6.7 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 156 | 4.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
b4qb <- as.factor(d[,"b4qb"])
new.d <- data.frame(new.d, b4qb)
new.d <- apply_labels(new.d, b4qb = "Other Cancer age")
temp.d <- data.frame (new.d, b4qb)
result<-questionr::freq(temp.d$b4qb, total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Other Cancer Age")
| n | % | val% | |
|---|---|---|---|
| 10 | 1 | 0.0 | 0.0 |
| 12 | 1 | 0.0 | 0.0 |
| 16 | 1 | 0.0 | 0.0 |
| 18 | 1 | 0.0 | 0.0 |
| 19 | 1 | 0.0 | 0.0 |
| 2 | 1 | 0.0 | 0.0 |
| 20 | 1 | 0.0 | 0.0 |
| 22 | 1 | 0.0 | 0.0 |
| 24 | 1 | 0.0 | 0.0 |
| 30 | 1 | 0.0 | 0.0 |
| 35 | 1 | 0.0 | 0.0 |
| 36 | 1 | 0.0 | 0.0 |
| 38 | 1 | 0.0 | 0.0 |
| 39 | 1 | 0.0 | 0.0 |
| 40 | 2 | 0.1 | 0.1 |
| 41 | 1 | 0.0 | 0.0 |
| 42 | 3 | 0.1 | 0.1 |
| 43 | 3 | 0.1 | 0.1 |
| 44 | 4 | 0.1 | 0.1 |
| 45 | 1 | 0.0 | 0.0 |
| 47 | 2 | 0.1 | 0.1 |
| 48 | 1 | 0.0 | 0.0 |
| 49 | 6 | 0.2 | 0.2 |
| 50 | 7 | 0.2 | 0.2 |
| 51 | 3 | 0.1 | 0.1 |
| 52 | 2 | 0.1 | 0.1 |
| 54 | 7 | 0.2 | 0.2 |
| 55 | 7 | 0.2 | 0.2 |
| 56 | 7 | 0.2 | 0.2 |
| 57 | 3 | 0.1 | 0.1 |
| 58 | 12 | 0.3 | 0.3 |
| 59 | 4 | 0.1 | 0.1 |
| 60 | 13 | 0.4 | 0.4 |
| 61 | 11 | 0.3 | 0.3 |
| 62 | 10 | 0.3 | 0.3 |
| 63 | 10 | 0.3 | 0.3 |
| 64 | 5 | 0.1 | 0.1 |
| 65 | 6 | 0.2 | 0.2 |
| 66 | 8 | 0.2 | 0.2 |
| 67 | 6 | 0.2 | 0.2 |
| 68 | 8 | 0.2 | 0.2 |
| 69 | 8 | 0.2 | 0.2 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 6 | 0.2 | 0.2 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 4 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 6 | 0.2 | 0.2 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 1 | 0.0 | 0.0 |
| 77 | 1 | 0.0 | 0.0 |
| 78 | 1 | 0.0 | 0.0 |
| 79 | 1 | 0.0 | 0.0 |
| “NA” | 3355 | 94.3 | 94.3 |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 291 | 90.7 | 92.4 |
| Yes | 24 | 7.5 | 7.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 1 | 0.3 | 0.3 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 3 | 0.9 | 0.9 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 2 | 0.6 | 0.6 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 297 | 92.5 | 92.5 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 294 | 91.6 | 93.3 |
| Yes | 21 | 6.5 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 1 | 0.3 | 0.3 |
| 13 | 1 | 0.3 | 0.3 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 2 | 0.6 | 0.6 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 302 | 94.1 | 94.1 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 289 | 90.0 | 92.3 |
| Yes | 24 | 7.5 | 7.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.3 | 0.3 |
| 45 | 2 | 0.6 | 0.6 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 3 | 0.9 | 0.9 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 2 | 0.6 | 0.6 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 298 | 92.8 | 92.8 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 99 | 30.8 | 31.5 |
| Yes | 215 | 67.0 | 68.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 1 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.3 | 0.3 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.3 | 0.3 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.3 | 0.3 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 2 | 0.6 | 0.6 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.3 | 0.3 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 5 | 1.6 | 1.6 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 6 | 1.9 | 1.9 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 8 | 2.5 | 2.5 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 3 | 0.9 | 0.9 |
| 38 | 6 | 1.9 | 1.9 |
| 39 | 2 | 0.6 | 0.6 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 12 | 3.7 | 3.7 |
| 41 | 3 | 0.9 | 0.9 |
| 42 | 7 | 2.2 | 2.2 |
| 43 | 2 | 0.6 | 0.6 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 20 | 6.2 | 6.2 |
| 46 | 3 | 0.9 | 0.9 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 6 | 1.9 | 1.9 |
| 49 | 2 | 0.6 | 0.6 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 16 | 5.0 | 5.0 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 8 | 2.5 | 2.5 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 15 | 4.7 | 4.7 |
| 56 | 7 | 2.2 | 2.2 |
| 57 | 3 | 0.9 | 0.9 |
| 58 | 8 | 2.5 | 2.5 |
| 59 | 1 | 0.3 | 0.3 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 11 | 3.4 | 3.4 |
| 61 | 4 | 1.2 | 1.2 |
| 62 | 6 | 1.9 | 1.9 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 9 | 2.8 | 2.8 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 4 | 1.2 | 1.2 |
| 69 | 1 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 2 | 0.6 | 0.6 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.3 | 0.3 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 1 | 0.3 | 0.3 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 1 | 0.3 | 0.3 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 122 | 38.0 | 38.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 301 | 93.8 | 96.8 |
| Yes | 10 | 3.1 | 3.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.3 | 0.3 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 3 | 0.9 | 0.9 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 2 | 0.6 | 0.6 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 3 | 0.9 | 0.9 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 304 | 94.7 | 94.7 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 141 | 43.9 | 44.9 |
| Yes | 172 | 53.6 | 54.8 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 1 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.3 | 0.3 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 4 | 1.2 | 1.2 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 2 | 0.6 | 0.6 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 6 | 1.9 | 1.9 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 5 | 1.6 | 1.6 |
| 43 | 2 | 0.6 | 0.6 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 8 | 2.5 | 2.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 4 | 1.2 | 1.2 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 1 | 0.3 | 0.3 |
| 50 | 18 | 5.6 | 5.6 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 7 | 2.2 | 2.2 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 16 | 5.0 | 5.0 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 14 | 4.4 | 4.4 |
| 59 | 2 | 0.6 | 0.6 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 14 | 4.4 | 4.4 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 6 | 1.9 | 1.9 |
| 63 | 3 | 0.9 | 0.9 |
| 64 | 4 | 1.2 | 1.2 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 3 | 0.9 | 0.9 |
| 69 | 4 | 1.2 | 1.2 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 2 | 0.6 | 0.6 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 2 | 0.6 | 0.6 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.3 | 0.3 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 1 | 0.3 | 0.3 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 170 | 53.0 | 53.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 270 | 84.1 | 84.9 |
| Yes | 48 | 15.0 | 15.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 1 | 0.3 | 0.3 |
| 10 | 3 | 0.9 | 0.9 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.3 | 0.3 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.3 | 0.3 |
| 15 | 1 | 0.3 | 0.3 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.3 | 0.3 |
| 21 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 3 | 0.9 | 0.9 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 4 | 1.2 | 1.2 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 1 | 0.3 | 0.3 |
| 6 | 3 | 0.9 | 0.9 |
| 60 | 4 | 1.2 | 1.2 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 1 | 0.3 | 0.3 |
| 7 | 2 | 0.6 | 0.6 |
| 70 | 2 | 0.6 | 0.6 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 1 | 0.3 | 0.3 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 4 | 1.2 | 1.2 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 275 | 85.7 | 85.7 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 290 | 90.3 | 91.5 |
| Yes | 27 | 8.4 | 8.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 1 | 0.3 | 0.3 |
| 13 | 1 | 0.3 | 0.3 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 1 | 0.3 | 0.3 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 2 | 0.6 | 0.6 |
| 23 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 2 | 0.6 | 0.6 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 2 | 0.6 | 0.6 |
| 3 | 1 | 0.3 | 0.3 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 297 | 92.5 | 92.5 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 304 | 94.7 | 96.2 |
| Yes | 12 | 3.7 | 3.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.3 | 0.3 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 2 | 0.6 | 0.6 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 2 | 0.6 | 0.6 |
| 41 | 1 | 0.3 | 0.3 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 85 | 0 | 0.0 | 0.0 |
| “NA” | 310 | 96.6 | 96.6 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 228 | 71.0 | 72.2 |
| Yes | 88 | 27.4 | 27.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 2 | 0.6 | 0.6 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 1 | 0.3 | 0.3 |
| 30 | 2 | 0.6 | 0.6 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 3 | 0.9 | 0.9 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 8 | 2.5 | 2.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 3 | 0.9 | 0.9 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 2 | 0.6 | 0.6 |
| 53 | 2 | 0.6 | 0.6 |
| 54 | 4 | 1.2 | 1.2 |
| 55 | 6 | 1.9 | 1.9 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 5 | 1.6 | 1.6 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 4 | 1.2 | 1.2 |
| 61 | 4 | 1.2 | 1.2 |
| 62 | 7 | 2.2 | 2.2 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 5 | 1.6 | 1.6 |
| 66 | 4 | 1.2 | 1.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.3 | 0.3 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 1 | 0.3 | 0.3 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 1 | 0.3 | 0.3 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 241 | 75.1 | 75.1 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 302 | 94.1 | 95 |
| Yes | 16 | 5.0 | 5 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 1 | 0.3 | 0.3 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.3 | 0.3 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 306 | 95.3 | 95.3 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 310 | 96.6 | 97.5 |
| Yes | 8 | 2.5 | 2.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.6 | 0.6 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| “NA” | 314 | 97.8 | 97.8 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 268 | 83.5 | 84.8 |
| Yes | 47 | 14.6 | 14.9 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.3 | 0.3 |
| 10 | 1 | 0.3 | 0.3 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 30 | 1 | 0.3 | 0.3 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 3 | 0.9 | 0.9 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 5 | 1.6 | 1.6 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 3 | 0.9 | 0.9 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 3 | 0.9 | 0.9 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 3 | 0.9 | 0.9 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 280 | 87.2 | 87.2 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 317 | 98.8 | 99.4 |
| Yes | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 319 | 99.4 | 99.4 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 276 | 86.0 | 86.8 |
| Yes | 42 | 13.1 | 13.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 2 | 0.6 | 0.6 |
| 26 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 3 | 0.9 | 0.9 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.3 | 0.3 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 4 | 1.2 | 1.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.3 | 0.3 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| “NA” | 292 | 91.0 | 91.0 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 316 | 98.4 | 99.1 |
| Yes | 3 | 0.9 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 36 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 9 | 0 | 0.0 | 0.0 |
| 90 | 0 | 0.0 | 0.0 |
| “NA” | 319 | 99.4 | 99.4 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 296 | 92.2 | 94.9 |
| Yes | 16 | 5.0 | 5.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 2 | 0.6 | 0.6 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 0.3 | 0.3 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 304 | 94.7 | 94.7 |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 189 | 90.0 | 96.4 |
| Yes | 7 | 3.3 | 3.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 9 | 4.3 | 4.3 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 3 | 1.4 | 1.4 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.5 | 0.5 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 1.0 | 1.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 195 | 92.9 | 92.9 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 182 | 86.7 | 91.9 |
| Yes | 16 | 7.6 | 8.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 5.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.5 | 0.5 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.5 | 0.5 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.5 | 0.5 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.5 | 0.5 |
| 60 | 2 | 1.0 | 1.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.5 | 0.5 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.5 | 0.5 |
| 68 | 1 | 0.5 | 0.5 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.5 | 0.5 |
| 77 | 1 | 0.5 | 0.5 |
| 78 | 1 | 0.5 | 0.5 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 197 | 93.8 | 93.8 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 186 | 88.6 | 94.9 |
| Yes | 10 | 4.8 | 5.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 9 | 4.3 | 4.3 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 1.0 | 1.0 |
| 61 | 3 | 1.4 | 1.4 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.5 | 0.5 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.5 | 0.5 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 192 | 91.4 | 91.4 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 66 | 31.4 | 33.5 |
| Yes | 131 | 62.4 | 66.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 6.2 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.5 | 0.5 |
| 20 | 1 | 0.5 | 0.5 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.5 | 0.5 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.5 | 0.5 |
| 29 | 1 | 0.5 | 0.5 |
| 30 | 2 | 1.0 | 1.0 |
| 31 | 1 | 0.5 | 0.5 |
| 32 | 1 | 0.5 | 0.5 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 3 | 1.4 | 1.4 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 1 | 0.5 | 0.5 |
| 38 | 1 | 0.5 | 0.5 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 12 | 5.7 | 5.7 |
| 41 | 1 | 0.5 | 0.5 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 3 | 1.4 | 1.4 |
| 44 | 1 | 0.5 | 0.5 |
| 45 | 5 | 2.4 | 2.4 |
| 46 | 1 | 0.5 | 0.5 |
| 47 | 3 | 1.4 | 1.4 |
| 48 | 3 | 1.4 | 1.4 |
| 49 | 1 | 0.5 | 0.5 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 18 | 8.6 | 8.6 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 1 | 0.5 | 0.5 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.5 | 0.5 |
| 55 | 10 | 4.8 | 4.8 |
| 56 | 1 | 0.5 | 0.5 |
| 57 | 1 | 0.5 | 0.5 |
| 58 | 4 | 1.9 | 1.9 |
| 59 | 3 | 1.4 | 1.4 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 14 | 6.7 | 6.7 |
| 61 | 4 | 1.9 | 1.9 |
| 62 | 3 | 1.4 | 1.4 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.5 | 0.5 |
| 66 | 1 | 0.5 | 0.5 |
| 67 | 1 | 0.5 | 0.5 |
| 68 | 1 | 0.5 | 0.5 |
| 69 | 1 | 0.5 | 0.5 |
| 7 | 1 | 0.5 | 0.5 |
| 70 | 1 | 0.5 | 0.5 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.5 | 0.5 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 97 | 46.2 | 46.2 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 189 | 90.0 | 96.9 |
| Yes | 5 | 2.4 | 2.6 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 1.0 | 1.0 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.5 | 0.5 |
| 61 | 1 | 0.5 | 0.5 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 204 | 97.1 | 97.1 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 113 | 53.8 | 60.4 |
| Yes | 74 | 35.2 | 39.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 23 | 11.0 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 2 | 1.0 | 1.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 3 | 1.4 | 1.4 |
| 41 | 1 | 0.5 | 0.5 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 5 | 2.4 | 2.4 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 1.0 | 1.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 7 | 3.3 | 3.3 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 1 | 0.5 | 0.5 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 2 | 1.0 | 1.0 |
| 55 | 8 | 3.8 | 3.8 |
| 56 | 2 | 1.0 | 1.0 |
| 57 | 2 | 1.0 | 1.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.5 | 0.5 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 10 | 4.8 | 4.8 |
| 61 | 2 | 1.0 | 1.0 |
| 62 | 2 | 1.0 | 1.0 |
| 63 | 3 | 1.4 | 1.4 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 3 | 1.4 | 1.4 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.5 | 0.5 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 0.5 | 0.5 |
| 70 | 3 | 1.4 | 1.4 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.5 | 0.5 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 147 | 70.0 | 70.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 173 | 82.4 | 84 |
| Yes | 33 | 15.7 | 16 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 2 | 1.0 | 1.0 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 1 | 0.5 | 0.5 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.5 | 0.5 |
| 20 | 1 | 0.5 | 0.5 |
| 21 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.5 | 0.5 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.5 | 0.5 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.5 | 0.5 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.5 | 0.5 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 2 | 1.0 | 1.0 |
| 40 | 1 | 0.5 | 0.5 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.5 | 0.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 2 | 1.0 | 1.0 |
| 50 | 3 | 1.4 | 1.4 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.5 | 0.5 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.5 | 0.5 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.5 | 0.5 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 2 | 1.0 | 1.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.5 | 0.5 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 2 | 1.0 | 1.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.5 | 0.5 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.5 | 0.5 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.5 | 0.5 |
| 77 | 1 | 0.5 | 0.5 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.5 | 0.5 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 179 | 85.2 | 85.2 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 196 | 93.3 | 96.6 |
| Yes | 7 | 3.3 | 3.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 3.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 9 | 4.3 | 4.3 |
| 10 | 0 | 0.0 | 0.0 |
| 13 | 1 | 0.5 | 0.5 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.5 | 0.5 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.5 | 0.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.5 | 0.5 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.5 | 0.5 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.5 | 0.5 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 195 | 92.9 | 92.9 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 192 | 91.4 | 94.6 |
| Yes | 11 | 5.2 | 5.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 3.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.5 | 0.5 |
| 45 | 1 | 0.5 | 0.5 |
| 46 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.5 | 0.5 |
| 50 | 2 | 1.0 | 1.0 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.5 | 0.5 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.5 | 0.5 |
| 71 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.5 | 0.5 |
| 79 | 0 | 0.0 | 0.0 |
| 85 | 0 | 0.0 | 0.0 |
| “NA” | 200 | 95.2 | 95.2 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 154 | 73.3 | 75.1 |
| Yes | 51 | 24.3 | 24.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.5 | 0.5 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.5 | 0.5 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 2 | 1.0 | 1.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.5 | 0.5 |
| 45 | 3 | 1.4 | 1.4 |
| 46 | 1 | 0.5 | 0.5 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.5 | 0.5 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 3 | 1.4 | 1.4 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 2 | 1.0 | 1.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 5 | 2.4 | 2.4 |
| 56 | 4 | 1.9 | 1.9 |
| 57 | 1 | 0.5 | 0.5 |
| 58 | 2 | 1.0 | 1.0 |
| 59 | 1 | 0.5 | 0.5 |
| 60 | 6 | 2.9 | 2.9 |
| 61 | 3 | 1.4 | 1.4 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.5 | 0.5 |
| 64 | 2 | 1.0 | 1.0 |
| 65 | 1 | 0.5 | 0.5 |
| 66 | 1 | 0.5 | 0.5 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.5 | 0.5 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.5 | 0.5 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.5 | 0.5 |
| 76 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 165 | 78.6 | 78.6 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 191 | 91.0 | 93.2 |
| Yes | 14 | 6.7 | 6.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 2 | 1.0 | 1.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.5 | 0.5 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 2 | 1.0 | 1.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.5 | 0.5 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 1 | 0.5 | 0.5 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 202 | 96.2 | 96.2 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 196 | 93.3 | 96.1 |
| Yes | 8 | 3.8 | 3.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0.0 | 0.0 |
| 21 | 1 | 0.5 | 0.5 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.5 | 0.5 |
| 55 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 1.0 | 1.0 |
| 69 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| “NA” | 206 | 98.1 | 98.1 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 182 | 86.7 | 88.8 |
| Yes | 23 | 11.0 | 11.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 1 | 0.5 | 0.5 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 3 | 1.4 | 1.4 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.5 | 0.5 |
| 55 | 2 | 1.0 | 1.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 2 | 1.0 | 1.0 |
| 59 | 1 | 0.5 | 0.5 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 2 | 1.0 | 1.0 |
| 64 | 2 | 1.0 | 1.0 |
| 65 | 2 | 1.0 | 1.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.5 | 0.5 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.5 | 0.5 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.5 | 0.5 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 191 | 91.0 | 91.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 200 | 95.2 | 98 |
| Yes | 4 | 1.9 | 2 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.5 | 0.5 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 209 | 99.5 | 99.5 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 178 | 84.8 | 88.6 |
| Yes | 22 | 10.5 | 10.9 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 9 | 4.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.5 | 0.5 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.5 | 0.5 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.5 | 0.5 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.5 | 0.5 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.5 | 0.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 1.0 | 1.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 2 | 1.0 | 1.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 1 | 0.5 | 0.5 |
| 60 | 2 | 1.0 | 1.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.5 | 0.5 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.5 | 0.5 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.5 | 0.5 |
| 72 | 1 | 0.5 | 0.5 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| “NA” | 193 | 91.9 | 91.9 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 196 | 93.3 | 96.1 |
| Yes | 8 | 3.8 | 3.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 9 | 4.3 | 4.3 |
| 25 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.5 | 0.5 |
| 45 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.5 | 0.5 |
| 49 | 1 | 0.5 | 0.5 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 90 | 0 | 0.0 | 0.0 |
| “NA” | 197 | 93.8 | 93.8 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 179 | 85.2 | 92.7 |
| Yes | 13 | 6.2 | 6.7 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 17 | 8.1 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.5 | 0.5 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.5 | 0.5 |
| 49 | 1 | 0.5 | 0.5 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.5 | 0.5 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.5 | 0.5 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 1 | 0.5 | 0.5 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.5 | 0.5 |
| 67 | 2 | 1.0 | 1.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 2 | 1.0 | 1.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.5 | 0.5 |
| 72 | 1 | 0.5 | 0.5 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 197 | 93.8 | 93.8 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 277 | 87.9 | 92.6 |
| Yes | 22 | 7.0 | 7.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 4 | 1.3 | 1.3 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 1 | 0.3 | 0.3 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 2 | 0.6 | 0.6 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 3 | 1.0 | 1.0 |
| 59 | 2 | 0.6 | 0.6 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 2 | 0.6 | 0.6 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 2 | 0.6 | 0.6 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 289 | 91.7 | 91.7 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 274 | 87.0 | 93.2 |
| Yes | 20 | 6.3 | 6.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 6.7 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 1 | 0.3 | 0.3 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 3 | 1.0 | 1.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 2 | 0.6 | 0.6 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 293 | 93.0 | 93.0 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 271 | 86.0 | 91.6 |
| Yes | 25 | 7.9 | 8.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 19 | 6.0 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 1.6 | 1.6 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 286 | 90.8 | 90.8 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 89 | 28.3 | 29.6 |
| Yes | 212 | 67.3 | 70.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| .35 | 1 | 0.3 | 0.3 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 2 | 0.6 | 0.6 |
| 22 | 2 | 0.6 | 0.6 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.3 | 0.3 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 2 | 0.6 | 0.6 |
| 30 | 5 | 1.6 | 1.6 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 2 | 0.6 | 0.6 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 5 | 1.6 | 1.6 |
| 36 | 4 | 1.3 | 1.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 12 | 3.8 | 3.8 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.3 | 0.3 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 16 | 5.1 | 5.1 |
| 46 | 3 | 1.0 | 1.0 |
| 47 | 2 | 0.6 | 0.6 |
| 48 | 3 | 1.0 | 1.0 |
| 49 | 3 | 1.0 | 1.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 28 | 8.9 | 8.9 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 2 | 0.6 | 0.6 |
| 54 | 10 | 3.2 | 3.2 |
| 55 | 30 | 9.5 | 9.5 |
| 56 | 3 | 1.0 | 1.0 |
| 57 | 3 | 1.0 | 1.0 |
| 58 | 4 | 1.3 | 1.3 |
| 59 | 3 | 1.0 | 1.0 |
| 6 | 1 | 0.3 | 0.3 |
| 60 | 11 | 3.5 | 3.5 |
| 61 | 6 | 1.9 | 1.9 |
| 62 | 6 | 1.9 | 1.9 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 3 | 1.0 | 1.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 3 | 1.0 | 1.0 |
| 69 | 2 | 0.6 | 0.6 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 1 | 0.3 | 0.3 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 1 | 0.3 | 0.3 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 2 | 0.6 | 0.6 |
| “NA” | 113 | 35.9 | 35.9 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 266 | 84.4 | 92.7 |
| Yes | 21 | 6.7 | 7.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 8.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 1 | 0.3 | 0.3 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.6 | 0.6 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 3 | 1.0 | 1.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 3 | 1.0 | 1.0 |
| 69 | 1 | 0.3 | 0.3 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 290 | 92.1 | 92.1 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 141 | 44.8 | 47.5 |
| Yes | 156 | 49.5 | 52.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 5.7 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.3 | 0.3 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 1 | 0.3 | 0.3 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.3 | 0.3 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 2 | 0.6 | 0.6 |
| 36 | 3 | 1.0 | 1.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 9 | 2.9 | 2.9 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.6 | 0.6 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 2 | 0.6 | 0.6 |
| 45 | 13 | 4.1 | 4.1 |
| 46 | 2 | 0.6 | 0.6 |
| 47 | 4 | 1.3 | 1.3 |
| 48 | 3 | 1.0 | 1.0 |
| 49 | 1 | 0.3 | 0.3 |
| 5 | 1 | 0.3 | 0.3 |
| 50 | 19 | 6.0 | 6.0 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 4 | 1.3 | 1.3 |
| 54 | 6 | 1.9 | 1.9 |
| 55 | 13 | 4.1 | 4.1 |
| 56 | 3 | 1.0 | 1.0 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 3 | 1.0 | 1.0 |
| 59 | 2 | 0.6 | 0.6 |
| 6 | 1 | 0.3 | 0.3 |
| 60 | 11 | 3.5 | 3.5 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 3 | 1.0 | 1.0 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 3 | 1.0 | 1.0 |
| 65 | 5 | 1.6 | 1.6 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 2 | 0.6 | 0.6 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 2 | 0.6 | 0.6 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 2 | 0.6 | 0.6 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 1 | 0.3 | 0.3 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 174 | 55.2 | 55.2 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 254 | 80.6 | 83 |
| Yes | 52 | 16.5 | 17 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 9 | 2.9 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 06 | 2 | 0.6 | 0.6 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.3 | 0.3 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.3 | 0.3 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.3 | 0.3 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 1 | 0.3 | 0.3 |
| 30 | 2 | 0.6 | 0.6 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 6 | 1.9 | 1.9 |
| 50 | 5 | 1.6 | 1.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 3 | 1.0 | 1.0 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 2 | 0.6 | 0.6 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.3 | 0.3 |
| 7 | 5 | 1.6 | 1.6 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.3 | 0.3 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.3 | 0.3 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 1 | 0.3 | 0.3 |
| “NA” | 266 | 84.4 | 84.4 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 283 | 89.8 | 94 |
| Yes | 18 | 5.7 | 6 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 1.6 | 1.6 |
| 10 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 1 | 0.3 | 0.3 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.3 | 0.3 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 1 | 0.3 | 0.3 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 3 | 1.0 | 1.0 |
| 36 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.6 | 0.6 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 294 | 93.3 | 93.3 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 294 | 93.3 | 97.7 |
| Yes | 7 | 2.2 | 2.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 15 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 85 | 0 | 0.0 | 0.0 |
| “NA” | 310 | 98.4 | 98.4 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 214 | 67.9 | 69.9 |
| Yes | 92 | 29.2 | 30.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 2 | 0.6 | 0.6 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 3 | 1 | 0.3 | 0.3 |
| 30 | 1 | 0.3 | 0.3 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 1 | 0.3 | 0.3 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 40 | 4 | 1.3 | 1.3 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.6 | 0.6 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 2 | 0.6 | 0.6 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 8 | 2.5 | 2.5 |
| 51 | 3 | 1.0 | 1.0 |
| 52 | 2 | 0.6 | 0.6 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 8 | 2.5 | 2.5 |
| 56 | 3 | 1.0 | 1.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 3 | 1.0 | 1.0 |
| 59 | 3 | 1.0 | 1.0 |
| 60 | 8 | 2.5 | 2.5 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 2 | 0.6 | 0.6 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 7 | 2.2 | 2.2 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 3 | 1.0 | 1.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.3 | 0.3 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 1 | 0.3 | 0.3 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 233 | 74.0 | 74.0 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 285 | 90.5 | 94.4 |
| Yes | 16 | 5.1 | 5.3 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 3 | 1.0 | 1.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 2 | 0.6 | 0.6 |
| 72 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.3 | 0.3 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 302 | 95.9 | 95.9 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 294 | 93.3 | 97 |
| Yes | 9 | 2.9 | 3 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| “NA” | 311 | 98.7 | 98.7 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 277 | 87.9 | 92.6 |
| Yes | 21 | 6.7 | 7.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.3 | 0.3 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 2 | 0.6 | 0.6 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 4 | 1.3 | 1.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 3 | 1.0 | 1.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 294 | 93.3 | 93.3 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 301 | 95.6 | 99 |
| Yes | 3 | 1.0 | 1 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 60 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 311 | 98.7 | 98.7 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 271 | 86.0 | 89.7 |
| Yes | 31 | 9.8 | 10.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.3 | 0.3 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 2 | 0.6 | 0.6 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.3 | 0.3 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.6 | 0.6 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 3 | 1.0 | 1.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| “NA” | 290 | 92.1 | 92.1 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 300 | 95.2 | 98.7 |
| Yes | 4 | 1.3 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 1.6 | 1.6 |
| 25 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.3 | 0.3 |
| 65 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.3 | 0.3 |
| 90 | 0 | 0.0 | 0.0 |
| “NA” | 307 | 97.5 | 97.5 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 277 | 87.9 | 93.6 |
| Yes | 19 | 6.0 | 6.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 19 | 6.0 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 1 | 0.3 | 0.3 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 4 | 1.3 | 1.3 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 3 | 1.0 | 1.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 298 | 94.6 | 94.6 |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 313 | 87.9 | 91.5 |
| Yes | 29 | 8.1 | 8.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 3.9 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 8 | 2.2 | 2.2 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.3 | 0.3 |
| 20 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 3 | 0.8 | 0.8 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 3 | 0.8 | 0.8 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 3 | 0.8 | 0.8 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.3 | 0.3 |
| 79 | 1 | 0.3 | 0.3 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 319 | 89.6 | 89.6 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 317 | 89.0 | 93.5 |
| Yes | 22 | 6.2 | 6.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.3 | 0.3 |
| 18 | 1 | 0.3 | 0.3 |
| 20 | 1 | 0.3 | 0.3 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 2 | 0.6 | 0.6 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 3 | 0.8 | 0.8 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 334 | 93.8 | 93.8 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 303 | 85.1 | 89.1 |
| Yes | 37 | 10.4 | 10.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 4.5 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 11 | 3.1 | 3.1 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.3 | 0.3 |
| 27 | 1 | 0.3 | 0.3 |
| 30 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.6 | 0.6 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 3 | 0.8 | 0.8 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 1 | 0.3 | 0.3 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 2 | 0.6 | 0.6 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 4 | 1.1 | 1.1 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 3 | 0.8 | 0.8 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 2 | 0.6 | 0.6 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 312 | 87.6 | 87.6 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 101 | 28.4 | 30 |
| Yes | 236 | 66.3 | 70 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 19 | 5.3 | NA |
| Total | 356 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 1 | 0.3 | 0.3 |
| 17 | 1 | 0.3 | 0.3 |
| 18 | 1 | 0.3 | 0.3 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 2 | 0.6 | 0.6 |
| 21 | 1 | 0.3 | 0.3 |
| 22 | 1 | 0.3 | 0.3 |
| 23 | 1 | 0.3 | 0.3 |
| 24 | 3 | 0.8 | 0.8 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 2 | 0.6 | 0.6 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 7 | 2.0 | 2.0 |
| 31 | 1 | 0.3 | 0.3 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 1 | 0.3 | 0.3 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 10 | 2.8 | 2.8 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 2 | 0.6 | 0.6 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 4 | 1 | 0.3 | 0.3 |
| 40 | 19 | 5.3 | 5.3 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 3 | 0.8 | 0.8 |
| 43 | 3 | 0.8 | 0.8 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 14 | 3.9 | 3.9 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 3 | 0.8 | 0.8 |
| 48 | 3 | 0.8 | 0.8 |
| 49 | 4 | 1.1 | 1.1 |
| 5 | 2 | 0.6 | 0.6 |
| 50 | 28 | 7.9 | 7.9 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 3 | 0.8 | 0.8 |
| 53 | 2 | 0.6 | 0.6 |
| 54 | 7 | 2.0 | 2.0 |
| 55 | 13 | 3.7 | 3.7 |
| 56 | 4 | 1.1 | 1.1 |
| 57 | 3 | 0.8 | 0.8 |
| 58 | 6 | 1.7 | 1.7 |
| 59 | 3 | 0.8 | 0.8 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 16 | 4.5 | 4.5 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 4 | 1.1 | 1.1 |
| 63 | 5 | 1.4 | 1.4 |
| 64 | 3 | 0.8 | 0.8 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 3 | 0.8 | 0.8 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 3 | 0.8 | 0.8 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 2 | 0.6 | 0.6 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 2 | 0.6 | 0.6 |
| 75 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 2 | 0.6 | 0.6 |
| 89 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.3 | 0.3 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 143 | 40.2 | 40.2 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 298 | 83.7 | 91.1 |
| Yes | 29 | 8.1 | 8.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 29 | 8.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 3 | 0.8 | 0.8 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.3 | 0.3 |
| 31 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 2 | 0.6 | 0.6 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 3 | 0.8 | 0.8 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.3 | 0.3 |
| 70 | 3 | 0.8 | 0.8 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 1 | 0.3 | 0.3 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 327 | 91.9 | 91.9 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 160 | 44.9 | 46.9 |
| Yes | 181 | 50.8 | 53.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.3 | 0.3 |
| 10 | 1 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 2 | 0.6 | 0.6 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 0.3 | 0.3 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 3 | 0.8 | 0.8 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 4 | 1.1 | 1.1 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 1 | 0.3 | 0.3 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 6 | 1.7 | 1.7 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.6 | 0.6 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 6 | 1.7 | 1.7 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 2 | 0.6 | 0.6 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 15 | 4.2 | 4.2 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 3 | 0.8 | 0.8 |
| 53 | 2 | 0.6 | 0.6 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 11 | 3.1 | 3.1 |
| 56 | 6 | 1.7 | 1.7 |
| 57 | 5 | 1.4 | 1.4 |
| 58 | 3 | 0.8 | 0.8 |
| 59 | 5 | 1.4 | 1.4 |
| 6 | 1 | 0.3 | 0.3 |
| 60 | 13 | 3.7 | 3.7 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 4 | 1.1 | 1.1 |
| 63 | 7 | 2.0 | 2.0 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 7 | 2.0 | 2.0 |
| 66 | 3 | 0.8 | 0.8 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 3 | 0.8 | 0.8 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.3 | 0.3 |
| 74 | 3 | 0.8 | 0.8 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.3 | 0.3 |
| 86 | 1 | 0.3 | 0.3 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 1 | 0.3 | 0.3 |
| “NA” | 212 | 59.6 | 59.6 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 283 | 79.5 | 80.4 |
| Yes | 68 | 19.1 | 19.3 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 4 | 1.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 3 | 0.8 | 0.8 |
| 10 | 3 | 0.8 | 0.8 |
| 11 | 1 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 2 | 0.6 | 0.6 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.3 | 0.3 |
| 19 | 2 | 0.6 | 0.6 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.3 | 0.3 |
| 21 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.3 | 0.3 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 4 | 1.1 | 1.1 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 6 | 1.7 | 1.7 |
| 57 | 4 | 1.1 | 1.1 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 1 | 0.3 | 0.3 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 4 | 1.1 | 1.1 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 2 | 0.6 | 0.6 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 2 | 0.6 | 0.6 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 1 | 0.3 | 0.3 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 1 | 0.3 | 0.3 |
| 79 | 1 | 0.3 | 0.3 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 1 | 0.3 | 0.3 |
| 9 | 1 | 0.3 | 0.3 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 295 | 82.9 | 82.9 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 321 | 90.2 | 90.9 |
| Yes | 32 | 9.0 | 9.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 10 | 2.8 | 2.8 |
| 10 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.3 | 0.3 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.3 | 0.3 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.3 | 0.3 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.3 | 0.3 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.3 | 0.3 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.3 | 0.3 |
| 9 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 324 | 91.0 | 91.0 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 339 | 95.2 | 98 |
| Yes | 7 | 2.0 | 2 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 85 | 0 | 0.0 | 0.0 |
| “NA” | 348 | 97.8 | 97.8 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 241 | 67.7 | 68.3 |
| Yes | 112 | 31.5 | 31.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.3 | 0.3 |
| 22 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 3 | 0.8 | 0.8 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 3 | 0.8 | 0.8 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 4 | 1.1 | 1.1 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 40 | 2 | 0.6 | 0.6 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 3 | 0.8 | 0.8 |
| 43 | 2 | 0.6 | 0.6 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 3 | 0.8 | 0.8 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 2 | 0.6 | 0.6 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 1 | 0.3 | 0.3 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 9 | 2.5 | 2.5 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 7 | 2.0 | 2.0 |
| 56 | 2 | 0.6 | 0.6 |
| 57 | 6 | 1.7 | 1.7 |
| 58 | 3 | 0.8 | 0.8 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 8 | 2.2 | 2.2 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 4 | 1.1 | 1.1 |
| 63 | 3 | 0.8 | 0.8 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 4 | 1.1 | 1.1 |
| 66 | 1 | 0.3 | 0.3 |
| 67 | 1 | 0.3 | 0.3 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 3 | 0.8 | 0.8 |
| 70 | 2 | 0.6 | 0.6 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 1 | 0.3 | 0.3 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 263 | 73.9 | 73.9 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 333 | 93.5 | 94.3 |
| Yes | 20 | 5.6 | 5.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 2 | 0.6 | 0.6 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 1 | 0.3 | 0.3 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.6 | 0.6 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 2 | 0.6 | 0.6 |
| 60 | 1 | 0.3 | 0.3 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 338 | 94.9 | 94.9 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 345 | 96.9 | 97.7 |
| Yes | 8 | 2.2 | 2.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 1 | 0.3 | 0.3 |
| 21 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.3 | 0.3 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.3 | 0.3 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 1 | 0.3 | 0.3 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| “NA” | 348 | 97.8 | 97.8 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 298 | 83.7 | 84.9 |
| Yes | 53 | 14.9 | 15.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.4 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 2 | 0.6 | 0.6 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 1 | 0.3 | 0.3 |
| 40 | 3 | 0.8 | 0.8 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 3 | 0.8 | 0.8 |
| 45 | 1 | 0.3 | 0.3 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 4 | 1.1 | 1.1 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 3 | 0.8 | 0.8 |
| 55 | 5 | 1.4 | 1.4 |
| 56 | 3 | 0.8 | 0.8 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 5 | 1.4 | 1.4 |
| 61 | 1 | 0.3 | 0.3 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.3 | 0.3 |
| “NA” | 309 | 86.8 | 86.8 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 350 | 98.3 | 99.4 |
| Yes | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 53 | 1 | 0.3 | 0.3 |
| 57 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 355 | 99.7 | 99.7 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 296 | 83.1 | 84.3 |
| Yes | 55 | 15.4 | 15.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.4 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 1 | 0.3 | 0.3 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.3 | 0.3 |
| 20 | 3 | 0.8 | 0.8 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 1 | 0.3 | 0.3 |
| 26 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.3 | 0.3 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.3 | 0.3 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 1 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.3 | 0.3 |
| 43 | 1 | 0.3 | 0.3 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 2 | 0.6 | 0.6 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 4 | 1.1 | 1.1 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 1 | 0.3 | 0.3 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 1 | 0.3 | 0.3 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.3 | 0.3 |
| 64 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 1 | 0.3 | 0.3 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 1 | 0.3 | 0.3 |
| “NA” | 313 | 87.9 | 87.9 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 343 | 96.3 | 99.1 |
| Yes | 3 | 0.8 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 10 | 2.8 | 2.8 |
| 25 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 90 | 0 | 0.0 | 0.0 |
| “NA” | 343 | 96.3 | 96.3 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 319 | 89.6 | 93.8 |
| Yes | 21 | 5.9 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 4.5 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 1 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.3 | 0.3 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 2 | 0.6 | 0.6 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.3 | 0.3 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.3 | 0.3 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.3 | 0.3 |
| 59 | 2 | 0.6 | 0.6 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.3 | 0.3 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.3 | 0.3 |
| 66 | 3 | 0.8 | 0.8 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.3 | 0.3 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 336 | 94.4 | 94.4 |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 494 | 84.4 | 91.8 |
| Yes | 44 | 7.5 | 8.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 47 | 8.0 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.2 | 0.2 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.2 | 0.2 |
| 17 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.2 | 0.2 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.2 | 0.2 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 2 | 0.3 | 0.3 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.3 | 0.3 |
| 51 | 4 | 0.7 | 0.7 |
| 52 | 1 | 0.2 | 0.2 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 2 | 0.3 | 0.3 |
| 55 | 1 | 0.2 | 0.2 |
| 56 | 2 | 0.3 | 0.3 |
| 57 | 1 | 0.2 | 0.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 3 | 0.5 | 0.5 |
| 60 | 2 | 0.3 | 0.3 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.2 | 0.2 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 3 | 0.5 | 0.5 |
| 65 | 2 | 0.3 | 0.3 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 2 | 0.3 | 0.3 |
| 70 | 3 | 0.5 | 0.5 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.2 | 0.2 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.2 | 0.2 |
| 76 | 1 | 0.2 | 0.2 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 1 | 0.2 | 0.2 |
| “NA” | 544 | 93.0 | 93.0 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 496 | 84.8 | 93.4 |
| Yes | 35 | 6.0 | 6.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 54 | 9.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 2 | 0.3 | 0.3 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 0.2 | 0.2 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 3 | 0.5 | 0.5 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 1 | 0.2 | 0.2 |
| 55 | 3 | 0.5 | 0.5 |
| 56 | 3 | 0.5 | 0.5 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 4 | 0.7 | 0.7 |
| 60 | 1 | 0.2 | 0.2 |
| 61 | 1 | 0.2 | 0.2 |
| 62 | 1 | 0.2 | 0.2 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 1 | 0.2 | 0.2 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 2 | 0.3 | 0.3 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.2 | 0.2 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 1 | 0.2 | 0.2 |
| “NA” | 555 | 94.9 | 94.9 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 474 | 81.0 | 89.1 |
| Yes | 58 | 9.9 | 10.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 53 | 9.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 6 | 1.0 | 1.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.2 | 0.2 |
| 23 | 1 | 0.2 | 0.2 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.2 | 0.2 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 2 | 0.3 | 0.3 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.3 | 0.3 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 1 | 0.2 | 0.2 |
| 50 | 1 | 0.2 | 0.2 |
| 51 | 2 | 0.3 | 0.3 |
| 52 | 2 | 0.3 | 0.3 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 6 | 1.0 | 1.0 |
| 55 | 1 | 0.2 | 0.2 |
| 56 | 3 | 0.5 | 0.5 |
| 57 | 4 | 0.7 | 0.7 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 1 | 0.2 | 0.2 |
| 60 | 7 | 1.2 | 1.2 |
| 61 | 1 | 0.2 | 0.2 |
| 62 | 2 | 0.3 | 0.3 |
| 63 | 3 | 0.5 | 0.5 |
| 64 | 1 | 0.2 | 0.2 |
| 65 | 2 | 0.3 | 0.3 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.3 | 0.3 |
| 69 | 1 | 0.2 | 0.2 |
| 70 | 3 | 0.5 | 0.5 |
| 71 | 1 | 0.2 | 0.2 |
| 72 | 1 | 0.2 | 0.2 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 523 | 89.4 | 89.4 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 130 | 22.2 | 23.4 |
| Yes | 420 | 71.8 | 75.7 |
| Scantron_Error | 5 | 0.9 | 0.9 |
| NA | 30 | 5.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 2 | 0.3 | 0.3 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 1 | 0.2 | 0.2 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.2 | 0.2 |
| 19 | 1 | 0.2 | 0.2 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 3 | 0.5 | 0.5 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 1 | 0.2 | 0.2 |
| 24 | 1 | 0.2 | 0.2 |
| 25 | 3 | 0.5 | 0.5 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 2 | 0.3 | 0.3 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 6 | 1.0 | 1.0 |
| 31 | 2 | 0.3 | 0.3 |
| 32 | 1 | 0.2 | 0.2 |
| 33 | 2 | 0.3 | 0.3 |
| 34 | 1 | 0.2 | 0.2 |
| 35 | 6 | 1.0 | 1.0 |
| 36 | 4 | 0.7 | 0.7 |
| 37 | 1 | 0.2 | 0.2 |
| 38 | 5 | 0.9 | 0.9 |
| 39 | 3 | 0.5 | 0.5 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 20 | 3.4 | 3.4 |
| 41 | 2 | 0.3 | 0.3 |
| 42 | 5 | 0.9 | 0.9 |
| 43 | 3 | 0.5 | 0.5 |
| 44 | 4 | 0.7 | 0.7 |
| 45 | 23 | 3.9 | 3.9 |
| 46 | 6 | 1.0 | 1.0 |
| 47 | 2 | 0.3 | 0.3 |
| 48 | 10 | 1.7 | 1.7 |
| 49 | 5 | 0.9 | 0.9 |
| 5 | 2 | 0.3 | 0.3 |
| 50 | 46 | 7.9 | 7.9 |
| 51 | 7 | 1.2 | 1.2 |
| 52 | 4 | 0.7 | 0.7 |
| 53 | 2 | 0.3 | 0.3 |
| 54 | 7 | 1.2 | 1.2 |
| 55 | 17 | 2.9 | 2.9 |
| 56 | 16 | 2.7 | 2.7 |
| 57 | 9 | 1.5 | 1.5 |
| 58 | 12 | 2.1 | 2.1 |
| 59 | 9 | 1.5 | 1.5 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 35 | 6.0 | 6.0 |
| 61 | 4 | 0.7 | 0.7 |
| 62 | 10 | 1.7 | 1.7 |
| 63 | 3 | 0.5 | 0.5 |
| 64 | 6 | 1.0 | 1.0 |
| 65 | 11 | 1.9 | 1.9 |
| 66 | 4 | 0.7 | 0.7 |
| 67 | 4 | 0.7 | 0.7 |
| 68 | 3 | 0.5 | 0.5 |
| 69 | 1 | 0.2 | 0.2 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 8 | 1.4 | 1.4 |
| 71 | 3 | 0.5 | 0.5 |
| 72 | 3 | 0.5 | 0.5 |
| 73 | 2 | 0.3 | 0.3 |
| 74 | 1 | 0.2 | 0.2 |
| 75 | 1 | 0.2 | 0.2 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 1 | 0.2 | 0.2 |
| 8 | 1 | 0.2 | 0.2 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.2 | 0.2 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 1 | 0.2 | 0.2 |
| “NA” | 224 | 38.3 | 38.3 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 475 | 81.2 | 91.3 |
| Yes | 45 | 7.7 | 8.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 65 | 11.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 3 | 0.5 | 0.5 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.2 | 0.2 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 3 | 0.5 | 0.5 |
| 41 | 1 | 0.2 | 0.2 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 2 | 0.3 | 0.3 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 1 | 0.2 | 0.2 |
| 50 | 5 | 0.9 | 0.9 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 2 | 0.3 | 0.3 |
| 54 | 2 | 0.3 | 0.3 |
| 55 | 3 | 0.5 | 0.5 |
| 56 | 2 | 0.3 | 0.3 |
| 57 | 3 | 0.5 | 0.5 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 2 | 0.3 | 0.3 |
| 60 | 2 | 0.3 | 0.3 |
| 61 | 1 | 0.2 | 0.2 |
| 62 | 1 | 0.2 | 0.2 |
| 63 | 1 | 0.2 | 0.2 |
| 64 | 4 | 0.7 | 0.7 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 1 | 0.2 | 0.2 |
| 69 | 1 | 0.2 | 0.2 |
| 70 | 3 | 0.5 | 0.5 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 1 | 0.2 | 0.2 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.2 | 0.2 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 1 | 0.2 | 0.2 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 535 | 91.5 | 91.5 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 220 | 37.6 | 40.6 |
| Yes | 321 | 54.9 | 59.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 43 | 7.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 2 | 0.3 | 0.3 |
| 12 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.2 | 0.2 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.2 | 0.2 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.2 | 0.2 |
| 25 | 1 | 0.2 | 0.2 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.2 | 0.2 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 2 | 0.3 | 0.3 |
| 35 | 5 | 0.9 | 0.9 |
| 36 | 3 | 0.5 | 0.5 |
| 37 | 1 | 0.2 | 0.2 |
| 38 | 3 | 0.5 | 0.5 |
| 39 | 2 | 0.3 | 0.3 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 5 | 0.9 | 0.9 |
| 41 | 2 | 0.3 | 0.3 |
| 42 | 2 | 0.3 | 0.3 |
| 43 | 2 | 0.3 | 0.3 |
| 44 | 4 | 0.7 | 0.7 |
| 45 | 12 | 2.1 | 2.1 |
| 46 | 3 | 0.5 | 0.5 |
| 47 | 1 | 0.2 | 0.2 |
| 48 | 6 | 1.0 | 1.0 |
| 49 | 2 | 0.3 | 0.3 |
| 5 | 2 | 0.3 | 0.3 |
| 50 | 24 | 4.1 | 4.1 |
| 51 | 7 | 1.2 | 1.2 |
| 52 | 6 | 1.0 | 1.0 |
| 53 | 4 | 0.7 | 0.7 |
| 54 | 8 | 1.4 | 1.4 |
| 55 | 21 | 3.6 | 3.6 |
| 56 | 9 | 1.5 | 1.5 |
| 57 | 7 | 1.2 | 1.2 |
| 58 | 5 | 0.9 | 0.9 |
| 59 | 6 | 1.0 | 1.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 24 | 4.1 | 4.1 |
| 61 | 7 | 1.2 | 1.2 |
| 62 | 11 | 1.9 | 1.9 |
| 63 | 4 | 0.7 | 0.7 |
| 64 | 5 | 0.9 | 0.9 |
| 65 | 11 | 1.9 | 1.9 |
| 66 | 2 | 0.3 | 0.3 |
| 67 | 2 | 0.3 | 0.3 |
| 68 | 7 | 1.2 | 1.2 |
| 69 | 3 | 0.5 | 0.5 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 8 | 1.4 | 1.4 |
| 71 | 3 | 0.5 | 0.5 |
| 72 | 1 | 0.2 | 0.2 |
| 73 | 2 | 0.3 | 0.3 |
| 74 | 1 | 0.2 | 0.2 |
| 75 | 3 | 0.5 | 0.5 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.2 | 0.2 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 1 | 0.2 | 0.2 |
| “NA” | 327 | 55.9 | 55.9 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 472 | 80.7 | 83.5 |
| Yes | 92 | 15.7 | 16.3 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 20 | 3.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 2 | 0.3 | 0.3 |
| 10 | 2 | 0.3 | 0.3 |
| 11 | 2 | 0.3 | 0.3 |
| 12 | 3 | 0.5 | 0.5 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 2 | 0.3 | 0.3 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 2 | 0.3 | 0.3 |
| 20 | 3 | 0.5 | 0.5 |
| 21 | 1 | 0.2 | 0.2 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 1 | 0.2 | 0.2 |
| 30 | 1 | 0.2 | 0.2 |
| 31 | 1 | 0.2 | 0.2 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.2 | 0.2 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.2 | 0.2 |
| 4 | 2 | 0.3 | 0.3 |
| 40 | 1 | 0.2 | 0.2 |
| 42 | 1 | 0.2 | 0.2 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.2 | 0.2 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.2 | 0.2 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 6 | 1.0 | 1.0 |
| 51 | 2 | 0.3 | 0.3 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 1 | 0.2 | 0.2 |
| 55 | 2 | 0.3 | 0.3 |
| 56 | 2 | 0.3 | 0.3 |
| 57 | 2 | 0.3 | 0.3 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 1 | 0.2 | 0.2 |
| 6 | 2 | 0.3 | 0.3 |
| 60 | 7 | 1.2 | 1.2 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 2 | 0.3 | 0.3 |
| 63 | 4 | 0.7 | 0.7 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 2 | 0.3 | 0.3 |
| 66 | 2 | 0.3 | 0.3 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 1 | 0.2 | 0.2 |
| 69 | 1 | 0.2 | 0.2 |
| 7 | 2 | 0.3 | 0.3 |
| 70 | 3 | 0.5 | 0.5 |
| 71 | 1 | 0.2 | 0.2 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.2 | 0.2 |
| 74 | 1 | 0.2 | 0.2 |
| 75 | 2 | 0.3 | 0.3 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 2 | 0.3 | 0.3 |
| 80 | 1 | 0.2 | 0.2 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 93 | 1 | 0.2 | 0.2 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 503 | 86.0 | 86.0 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 503 | 86.0 | 90.3 |
| Yes | 53 | 9.1 | 9.5 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 28 | 4.8 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 2 | 0.3 | 0.3 |
| 10 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 1 | 0.2 | 0.2 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.2 | 0.2 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 2 | 0.3 | 0.3 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.2 | 0.2 |
| 25 | 2 | 0.3 | 0.3 |
| 27 | 1 | 0.2 | 0.2 |
| 28 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 5 | 0.9 | 0.9 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 4 | 0.7 | 0.7 |
| 36 | 1 | 0.2 | 0.2 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.2 | 0.2 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.3 | 0.3 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 2 | 0.3 | 0.3 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.2 | 0.2 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 4 | 0.7 | 0.7 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.2 | 0.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.2 | 0.2 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 1 | 0.2 | 0.2 |
| 60 | 5 | 0.9 | 0.9 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.2 | 0.2 |
| 63 | 1 | 0.2 | 0.2 |
| 64 | 1 | 0.2 | 0.2 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 1 | 0.2 | 0.2 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 1 | 0.2 | 0.2 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.2 | 0.2 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.2 | 0.2 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 534 | 91.3 | 91.3 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 542 | 92.6 | 97 |
| Yes | 17 | 2.9 | 3 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 26 | 4.4 | NA |
| Total | 585 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.2 | 0.2 |
| 22 | 1 | 0.2 | 0.2 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 2 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.2 | 0.2 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 50 | 2 | 0.3 | 0.3 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.2 | 0.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 0.2 | 0.2 |
| 58 | 2 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.2 | 0.2 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.2 | 0.2 |
| 69 | 1 | 0.2 | 0.2 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 1 | 0.2 | 0.2 |
| 85 | 0 | 0.0 | 0.0 |
| “NA” | 569 | 97.3 | 97.3 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 366 | 62.6 | 64.6 |
| Yes | 200 | 34.2 | 35.3 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 18 | 3.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 3 | 0.5 | 0.5 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.2 | 0.2 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 1 | 0.2 | 0.2 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.2 | 0.2 |
| 18 | 1 | 0.2 | 0.2 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.2 | 0.2 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.2 | 0.2 |
| 36 | 2 | 0.3 | 0.3 |
| 37 | 1 | 0.2 | 0.2 |
| 38 | 2 | 0.3 | 0.3 |
| 39 | 1 | 0.2 | 0.2 |
| 40 | 7 | 1.2 | 1.2 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.2 | 0.2 |
| 43 | 3 | 0.5 | 0.5 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 7 | 1.2 | 1.2 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 5 | 0.9 | 0.9 |
| 49 | 3 | 0.5 | 0.5 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 12 | 2.1 | 2.1 |
| 51 | 3 | 0.5 | 0.5 |
| 52 | 3 | 0.5 | 0.5 |
| 53 | 3 | 0.5 | 0.5 |
| 54 | 4 | 0.7 | 0.7 |
| 55 | 16 | 2.7 | 2.7 |
| 56 | 5 | 0.9 | 0.9 |
| 57 | 4 | 0.7 | 0.7 |
| 58 | 11 | 1.9 | 1.9 |
| 59 | 7 | 1.2 | 1.2 |
| 60 | 15 | 2.6 | 2.6 |
| 61 | 7 | 1.2 | 1.2 |
| 62 | 7 | 1.2 | 1.2 |
| 63 | 1 | 0.2 | 0.2 |
| 64 | 5 | 0.9 | 0.9 |
| 65 | 5 | 0.9 | 0.9 |
| 66 | 2 | 0.3 | 0.3 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 3 | 0.5 | 0.5 |
| 69 | 4 | 0.7 | 0.7 |
| 70 | 7 | 1.2 | 1.2 |
| 71 | 1 | 0.2 | 0.2 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.2 | 0.2 |
| 75 | 1 | 0.2 | 0.2 |
| 76 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 416 | 71.1 | 71.1 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 532 | 90.9 | 94.7 |
| Yes | 30 | 5.1 | 5.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 23 | 3.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 1 | 0.2 | 0.2 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.2 | 0.2 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.2 | 0.2 |
| 45 | 1 | 0.2 | 0.2 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.2 | 0.2 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 2 | 0.3 | 0.3 |
| 50 | 1 | 0.2 | 0.2 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 2 | 0.3 | 0.3 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.2 | 0.2 |
| 61 | 1 | 0.2 | 0.2 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 2 | 0.3 | 0.3 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 1 | 0.2 | 0.2 |
| 69 | 2 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.2 | 0.2 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.2 | 0.2 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.2 | 0.2 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 1 | 0.2 | 0.2 |
| “NA” | 560 | 95.7 | 95.7 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 550 | 94.0 | 97.7 |
| Yes | 13 | 2.2 | 2.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 22 | 3.8 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.2 | 0.2 |
| 48 | 1 | 0.2 | 0.2 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.2 | 0.2 |
| 58 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.2 | 0.2 |
| 61 | 1 | 0.2 | 0.2 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.2 | 0.2 |
| “NA” | 575 | 98.3 | 98.3 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 472 | 80.7 | 84.3 |
| Yes | 88 | 15.0 | 15.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.2 | 0.2 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 1 | 0.2 | 0.2 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.2 | 0.2 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 3 | 0.5 | 0.5 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 2 | 0.3 | 0.3 |
| 39 | 2 | 0.3 | 0.3 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 2 | 0.3 | 0.3 |
| 41 | 1 | 0.2 | 0.2 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 0.2 | 0.2 |
| 44 | 1 | 0.2 | 0.2 |
| 45 | 6 | 1.0 | 1.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 3 | 0.5 | 0.5 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 7 | 1.2 | 1.2 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 6 | 1.0 | 1.0 |
| 53 | 2 | 0.3 | 0.3 |
| 54 | 1 | 0.2 | 0.2 |
| 55 | 4 | 0.7 | 0.7 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 4 | 0.7 | 0.7 |
| 59 | 1 | 0.2 | 0.2 |
| 60 | 5 | 0.9 | 0.9 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 2 | 0.3 | 0.3 |
| 63 | 1 | 0.2 | 0.2 |
| 64 | 3 | 0.5 | 0.5 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 2 | 0.3 | 0.3 |
| 69 | 2 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 1 | 0.2 | 0.2 |
| 72 | 2 | 0.3 | 0.3 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.2 | 0.2 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 514 | 87.9 | 87.9 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 559 | 95.6 | 98.4 |
| Yes | 9 | 1.5 | 1.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 2.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.2 | 0.2 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.2 | 0.2 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 80 | 1 | 0.2 | 0.2 |
| “NA” | 581 | 99.3 | 99.3 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 486 | 83.1 | 87.1 |
| Yes | 72 | 12.3 | 12.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 27 | 4.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 2 | 0.3 | 0.3 |
| 21 | 2 | 0.3 | 0.3 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.2 | 0.2 |
| 28 | 1 | 0.2 | 0.2 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 2 | 0.3 | 0.3 |
| 32 | 1 | 0.2 | 0.2 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 2 | 0.3 | 0.3 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.2 | 0.2 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 4 | 0.7 | 0.7 |
| 41 | 1 | 0.2 | 0.2 |
| 42 | 3 | 0.5 | 0.5 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.2 | 0.2 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 2 | 0.3 | 0.3 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 6 | 1.0 | 1.0 |
| 51 | 1 | 0.2 | 0.2 |
| 52 | 2 | 0.3 | 0.3 |
| 53 | 1 | 0.2 | 0.2 |
| 54 | 1 | 0.2 | 0.2 |
| 55 | 3 | 0.5 | 0.5 |
| 56 | 1 | 0.2 | 0.2 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 1 | 0.2 | 0.2 |
| 59 | 1 | 0.2 | 0.2 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 3 | 0.5 | 0.5 |
| 61 | 2 | 0.3 | 0.3 |
| 62 | 3 | 0.5 | 0.5 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 3 | 0.5 | 0.5 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.3 | 0.3 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 3 | 0.5 | 0.5 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| “NA” | 526 | 89.9 | 89.9 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 562 | 96.1 | 99.5 |
| Yes | 3 | 0.5 | 0.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 20 | 3.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 2 | 0.3 | 0.3 |
| 25 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.2 | 0.2 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 90 | 0 | 0.0 | 0.0 |
| “NA” | 582 | 99.5 | 99.5 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 522 | 89.2 | 93.2 |
| Yes | 38 | 6.5 | 6.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.2 | 0.2 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.2 | 0.2 |
| 20 | 1 | 0.2 | 0.2 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 1 | 0.2 | 0.2 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 2 | 0.3 | 0.3 |
| 43 | 1 | 0.2 | 0.2 |
| 44 | 1 | 0.2 | 0.2 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 1 | 0.2 | 0.2 |
| 50 | 1 | 0.2 | 0.2 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.2 | 0.2 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 0.2 | 0.2 |
| 56 | 2 | 0.3 | 0.3 |
| 57 | 1 | 0.2 | 0.2 |
| 58 | 2 | 0.3 | 0.3 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 0.2 | 0.2 |
| 61 | 2 | 0.3 | 0.3 |
| 62 | 2 | 0.3 | 0.3 |
| 63 | 1 | 0.2 | 0.2 |
| 64 | 1 | 0.2 | 0.2 |
| 65 | 1 | 0.2 | 0.2 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 2 | 0.3 | 0.3 |
| 69 | 2 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.2 | 0.2 |
| 71 | 1 | 0.2 | 0.2 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 1 | 0.2 | 0.2 |
| “NA” | 552 | 94.4 | 94.4 |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1532 | 87.3 | 93.2 |
| Yes | 110 | 6.3 | 6.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 110 | 6.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 21 | 1.2 | 1.2 |
| 1 | 1 | 0.1 | 0.1 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.1 | 0.1 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.1 | 0.1 |
| 25 | 1 | 0.1 | 0.1 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 2 | 0.1 | 0.1 |
| 29 | 1 | 0.1 | 0.1 |
| 31 | 2 | 0.1 | 0.1 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 1 | 0.1 | 0.1 |
| 35 | 2 | 0.1 | 0.1 |
| 38 | 1 | 0.1 | 0.1 |
| 40 | 2 | 0.1 | 0.1 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.1 | 0.1 |
| 46 | 3 | 0.2 | 0.2 |
| 47 | 1 | 0.1 | 0.1 |
| 48 | 3 | 0.2 | 0.2 |
| 49 | 1 | 0.1 | 0.1 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 8 | 0.5 | 0.5 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 3 | 0.2 | 0.2 |
| 53 | 1 | 0.1 | 0.1 |
| 54 | 1 | 0.1 | 0.1 |
| 55 | 4 | 0.2 | 0.2 |
| 56 | 1 | 0.1 | 0.1 |
| 57 | 4 | 0.2 | 0.2 |
| 58 | 6 | 0.3 | 0.3 |
| 59 | 6 | 0.3 | 0.3 |
| 60 | 5 | 0.3 | 0.3 |
| 61 | 3 | 0.2 | 0.2 |
| 62 | 1 | 0.1 | 0.1 |
| 63 | 5 | 0.3 | 0.3 |
| 64 | 4 | 0.2 | 0.2 |
| 65 | 2 | 0.1 | 0.1 |
| 66 | 1 | 0.1 | 0.1 |
| 67 | 3 | 0.2 | 0.2 |
| 68 | 2 | 0.1 | 0.1 |
| 69 | 3 | 0.2 | 0.2 |
| 70 | 1 | 0.1 | 0.1 |
| 71 | 2 | 0.1 | 0.1 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 3 | 0.2 | 0.2 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 1637 | 93.3 | 93.3 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1516 | 86.4 | 93.5 |
| Yes | 105 | 6.0 | 6.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 133 | 7.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 1 | 0.1 | 0.1 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.1 | 0.1 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.1 | 0.1 |
| 31 | 1 | 0.1 | 0.1 |
| 34 | 1 | 0.1 | 0.1 |
| 35 | 1 | 0.1 | 0.1 |
| 39 | 1 | 0.1 | 0.1 |
| 40 | 2 | 0.1 | 0.1 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 2 | 0.1 | 0.1 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.1 | 0.1 |
| 48 | 3 | 0.2 | 0.2 |
| 49 | 5 | 0.3 | 0.3 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 2 | 0.1 | 0.1 |
| 51 | 1 | 0.1 | 0.1 |
| 52 | 3 | 0.2 | 0.2 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 4 | 0.2 | 0.2 |
| 56 | 1 | 0.1 | 0.1 |
| 57 | 2 | 0.1 | 0.1 |
| 58 | 5 | 0.3 | 0.3 |
| 59 | 4 | 0.2 | 0.2 |
| 60 | 4 | 0.2 | 0.2 |
| 61 | 3 | 0.2 | 0.2 |
| 62 | 4 | 0.2 | 0.2 |
| 63 | 2 | 0.1 | 0.1 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 6 | 0.3 | 0.3 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 3 | 0.2 | 0.2 |
| 68 | 2 | 0.1 | 0.1 |
| 69 | 5 | 0.3 | 0.3 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.1 | 0.1 |
| 71 | 1 | 0.1 | 0.1 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 1 | 0.1 | 0.1 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 1 | 0.1 | 0.1 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 1667 | 95.0 | 95.0 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1473 | 84.0 | 90.6 |
| Yes | 150 | 8.6 | 9.2 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 128 | 7.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 36 | 2.1 | 2.1 |
| 15 | 1 | 0.1 | 0.1 |
| 16 | 1 | 0.1 | 0.1 |
| 19 | 1 | 0.1 | 0.1 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.1 | 0.1 |
| 34 | 1 | 0.1 | 0.1 |
| 35 | 1 | 0.1 | 0.1 |
| 38 | 1 | 0.1 | 0.1 |
| 40 | 1 | 0.1 | 0.1 |
| 42 | 1 | 0.1 | 0.1 |
| 43 | 2 | 0.1 | 0.1 |
| 45 | 3 | 0.2 | 0.2 |
| 46 | 2 | 0.1 | 0.1 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 1 | 0.1 | 0.1 |
| 49 | 1 | 0.1 | 0.1 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 7 | 0.4 | 0.4 |
| 51 | 2 | 0.1 | 0.1 |
| 52 | 1 | 0.1 | 0.1 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 4 | 0.2 | 0.2 |
| 55 | 7 | 0.4 | 0.4 |
| 56 | 4 | 0.2 | 0.2 |
| 57 | 4 | 0.2 | 0.2 |
| 58 | 3 | 0.2 | 0.2 |
| 59 | 5 | 0.3 | 0.3 |
| 60 | 5 | 0.3 | 0.3 |
| 61 | 6 | 0.3 | 0.3 |
| 62 | 5 | 0.3 | 0.3 |
| 63 | 9 | 0.5 | 0.5 |
| 64 | 4 | 0.2 | 0.2 |
| 65 | 7 | 0.4 | 0.4 |
| 66 | 4 | 0.2 | 0.2 |
| 67 | 5 | 0.3 | 0.3 |
| 68 | 3 | 0.2 | 0.2 |
| 69 | 7 | 0.4 | 0.4 |
| 70 | 2 | 0.1 | 0.1 |
| 71 | 2 | 0.1 | 0.1 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 1 | 0.1 | 0.1 |
| 78 | 2 | 0.1 | 0.1 |
| 79 | 1 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| “NA” | 1593 | 90.8 | 90.8 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 398 | 22.7 | 23.8 |
| Yes | 1270 | 72.4 | 76.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 84 | 4.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 1 | 0.1 | 0.1 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 1 | 0.1 | 0.1 |
| 13 | 1 | 0.1 | 0.1 |
| 14 | 1 | 0.1 | 0.1 |
| 15 | 3 | 0.2 | 0.2 |
| 16 | 6 | 0.3 | 0.3 |
| 17 | 1 | 0.1 | 0.1 |
| 18 | 4 | 0.2 | 0.2 |
| 19 | 3 | 0.2 | 0.2 |
| 2 | 1 | 0.1 | 0.1 |
| 20 | 6 | 0.3 | 0.3 |
| 21 | 2 | 0.1 | 0.1 |
| 22 | 3 | 0.2 | 0.2 |
| 23 | 3 | 0.2 | 0.2 |
| 24 | 4 | 0.2 | 0.2 |
| 25 | 10 | 0.6 | 0.6 |
| 26 | 1 | 0.1 | 0.1 |
| 27 | 5 | 0.3 | 0.3 |
| 28 | 6 | 0.3 | 0.3 |
| 29 | 1 | 0.1 | 0.1 |
| 30 | 37 | 2.1 | 2.1 |
| 31 | 9 | 0.5 | 0.5 |
| 32 | 4 | 0.2 | 0.2 |
| 33 | 4 | 0.2 | 0.2 |
| 34 | 4 | 0.2 | 0.2 |
| 35 | 47 | 2.7 | 2.7 |
| 36 | 10 | 0.6 | 0.6 |
| 37 | 4 | 0.2 | 0.2 |
| 38 | 10 | 0.6 | 0.6 |
| 39 | 7 | 0.4 | 0.4 |
| 4 | 1 | 0.1 | 0.1 |
| 40 | 90 | 5.1 | 5.1 |
| 41 | 5 | 0.3 | 0.3 |
| 42 | 18 | 1.0 | 1.0 |
| 43 | 7 | 0.4 | 0.4 |
| 44 | 9 | 0.5 | 0.5 |
| 45 | 76 | 4.3 | 4.3 |
| 46 | 12 | 0.7 | 0.7 |
| 47 | 10 | 0.6 | 0.6 |
| 48 | 17 | 1.0 | 1.0 |
| 49 | 14 | 0.8 | 0.8 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 115 | 6.6 | 6.6 |
| 51 | 11 | 0.6 | 0.6 |
| 52 | 28 | 1.6 | 1.6 |
| 53 | 11 | 0.6 | 0.6 |
| 54 | 24 | 1.4 | 1.4 |
| 55 | 80 | 4.6 | 4.6 |
| 56 | 21 | 1.2 | 1.2 |
| 57 | 18 | 1.0 | 1.0 |
| 58 | 28 | 1.6 | 1.6 |
| 59 | 18 | 1.0 | 1.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 76 | 4.3 | 4.3 |
| 61 | 15 | 0.9 | 0.9 |
| 62 | 24 | 1.4 | 1.4 |
| 63 | 12 | 0.7 | 0.7 |
| 64 | 19 | 1.1 | 1.1 |
| 65 | 30 | 1.7 | 1.7 |
| 66 | 6 | 0.3 | 0.3 |
| 67 | 14 | 0.8 | 0.8 |
| 68 | 12 | 0.7 | 0.7 |
| 69 | 9 | 0.5 | 0.5 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 15 | 0.9 | 0.9 |
| 71 | 9 | 0.5 | 0.5 |
| 72 | 3 | 0.2 | 0.2 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 1 | 0.1 | 0.1 |
| 77 | 1 | 0.1 | 0.1 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 2 | 0.1 | 0.1 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 1 | 0.1 | 0.1 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 1 | 0.1 | 0.1 |
| 94 | 1 | 0.1 | 0.1 |
| 96 | 1 | 0.1 | 0.1 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 1 | 0.1 | 0.1 |
| “NA” | 686 | 39.1 | 39.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1488 | 84.8 | 93.4 |
| Yes | 104 | 5.9 | 6.5 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 161 | 9.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.1 | 0.1 |
| ** | 1 | 0.1 | 0.1 |
| 0 | 16 | 0.9 | 0.9 |
| 1 | 1 | 0.1 | 0.1 |
| 16 | 1 | 0.1 | 0.1 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.1 | 0.1 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 1 | 0.1 | 0.1 |
| 30 | 1 | 0.1 | 0.1 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.1 | 0.1 |
| 34 | 2 | 0.1 | 0.1 |
| 35 | 4 | 0.2 | 0.2 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 1 | 0.1 | 0.1 |
| 40 | 7 | 0.4 | 0.4 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 3 | 0.2 | 0.2 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 0.1 | 0.1 |
| 48 | 1 | 0.1 | 0.1 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 8 | 0.5 | 0.5 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 0.1 | 0.1 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 3 | 0.2 | 0.2 |
| 55 | 8 | 0.5 | 0.5 |
| 56 | 1 | 0.1 | 0.1 |
| 57 | 1 | 0.1 | 0.1 |
| 58 | 5 | 0.3 | 0.3 |
| 59 | 3 | 0.2 | 0.2 |
| 60 | 14 | 0.8 | 0.8 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 6 | 0.3 | 0.3 |
| 63 | 2 | 0.1 | 0.1 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 10 | 0.6 | 0.6 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 5 | 0.3 | 0.3 |
| 68 | 3 | 0.2 | 0.2 |
| 69 | 3 | 0.2 | 0.2 |
| 70 | 1 | 0.1 | 0.1 |
| 71 | 1 | 0.1 | 0.1 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 2 | 0.1 | 0.1 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 1 | 0.1 | 0.1 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 1 | 0.1 | 0.1 |
| “NA” | 1624 | 92.6 | 92.6 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 720 | 41.0 | 44.0 |
| Yes | 916 | 52.2 | 56.0 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 117 | 6.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 2 | 0.1 | 0.1 |
| 10 | 1 | 0.1 | 0.1 |
| 12 | 1 | 0.1 | 0.1 |
| 14 | 1 | 0.1 | 0.1 |
| 15 | 1 | 0.1 | 0.1 |
| 16 | 2 | 0.1 | 0.1 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 1 | 0.1 | 0.1 |
| 2 | 1 | 0.1 | 0.1 |
| 20 | 1 | 0.1 | 0.1 |
| 21 | 2 | 0.1 | 0.1 |
| 22 | 1 | 0.1 | 0.1 |
| 24 | 3 | 0.2 | 0.2 |
| 25 | 3 | 0.2 | 0.2 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 3 | 0.2 | 0.2 |
| 28 | 4 | 0.2 | 0.2 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 10 | 0.6 | 0.6 |
| 31 | 4 | 0.2 | 0.2 |
| 32 | 3 | 0.2 | 0.2 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 3 | 0.2 | 0.2 |
| 35 | 18 | 1.0 | 1.0 |
| 36 | 8 | 0.5 | 0.5 |
| 37 | 2 | 0.1 | 0.1 |
| 38 | 9 | 0.5 | 0.5 |
| 39 | 2 | 0.1 | 0.1 |
| 4 | 1 | 0.1 | 0.1 |
| 40 | 45 | 2.6 | 2.6 |
| 41 | 3 | 0.2 | 0.2 |
| 42 | 3 | 0.2 | 0.2 |
| 43 | 4 | 0.2 | 0.2 |
| 44 | 4 | 0.2 | 0.2 |
| 45 | 42 | 2.4 | 2.4 |
| 46 | 8 | 0.5 | 0.5 |
| 47 | 7 | 0.4 | 0.4 |
| 48 | 12 | 0.7 | 0.7 |
| 49 | 7 | 0.4 | 0.4 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 90 | 5.1 | 5.1 |
| 51 | 7 | 0.4 | 0.4 |
| 52 | 12 | 0.7 | 0.7 |
| 53 | 9 | 0.5 | 0.5 |
| 54 | 18 | 1.0 | 1.0 |
| 55 | 65 | 3.7 | 3.7 |
| 56 | 16 | 0.9 | 0.9 |
| 57 | 22 | 1.3 | 1.3 |
| 58 | 14 | 0.8 | 0.8 |
| 59 | 16 | 0.9 | 0.9 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 66 | 3.8 | 3.8 |
| 61 | 11 | 0.6 | 0.6 |
| 62 | 31 | 1.8 | 1.8 |
| 63 | 10 | 0.6 | 0.6 |
| 64 | 11 | 0.6 | 0.6 |
| 65 | 24 | 1.4 | 1.4 |
| 66 | 7 | 0.4 | 0.4 |
| 67 | 11 | 0.6 | 0.6 |
| 68 | 8 | 0.5 | 0.5 |
| 69 | 16 | 0.9 | 0.9 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 14 | 0.8 | 0.8 |
| 71 | 2 | 0.1 | 0.1 |
| 72 | 8 | 0.5 | 0.5 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 3 | 0.2 | 0.2 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 3 | 0.2 | 0.2 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 1 | 0.1 | 0.1 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 1 | 0.1 | 0.1 |
| 96 | 1 | 0.1 | 0.1 |
| 97 | 1 | 0.1 | 0.1 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 1029 | 58.7 | 58.7 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1464 | 83.5 | 86.3 |
| Yes | 232 | 13.2 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 58 | 3.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 4 | 0.2 | 0.2 |
| 10 | 9 | 0.5 | 0.5 |
| 11 | 1 | 0.1 | 0.1 |
| 12 | 6 | 0.3 | 0.3 |
| 13 | 1 | 0.1 | 0.1 |
| 14 | 1 | 0.1 | 0.1 |
| 15 | 3 | 0.2 | 0.2 |
| 16 | 3 | 0.2 | 0.2 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 8 | 0.5 | 0.5 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 3 | 0.2 | 0.2 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 1 | 0.1 | 0.1 |
| 23 | 1 | 0.1 | 0.1 |
| 25 | 3 | 0.2 | 0.2 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 1 | 0.1 | 0.1 |
| 28 | 2 | 0.1 | 0.1 |
| 29 | 1 | 0.1 | 0.1 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 4 | 0.2 | 0.2 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 1 | 0.1 | 0.1 |
| 33 | 1 | 0.1 | 0.1 |
| 35 | 1 | 0.1 | 0.1 |
| 37 | 1 | 0.1 | 0.1 |
| 38 | 3 | 0.2 | 0.2 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 3 | 0.2 | 0.2 |
| 40 | 6 | 0.3 | 0.3 |
| 42 | 3 | 0.2 | 0.2 |
| 43 | 1 | 0.1 | 0.1 |
| 45 | 4 | 0.2 | 0.2 |
| 46 | 1 | 0.1 | 0.1 |
| 47 | 1 | 0.1 | 0.1 |
| 48 | 1 | 0.1 | 0.1 |
| 49 | 2 | 0.1 | 0.1 |
| 5 | 12 | 0.7 | 0.7 |
| 50 | 7 | 0.4 | 0.4 |
| 51 | 1 | 0.1 | 0.1 |
| 52 | 3 | 0.2 | 0.2 |
| 53 | 1 | 0.1 | 0.1 |
| 54 | 1 | 0.1 | 0.1 |
| 55 | 9 | 0.5 | 0.5 |
| 56 | 3 | 0.2 | 0.2 |
| 57 | 5 | 0.3 | 0.3 |
| 58 | 3 | 0.2 | 0.2 |
| 59 | 6 | 0.3 | 0.3 |
| 6 | 7 | 0.4 | 0.4 |
| 60 | 9 | 0.5 | 0.5 |
| 61 | 2 | 0.1 | 0.1 |
| 62 | 5 | 0.3 | 0.3 |
| 63 | 3 | 0.2 | 0.2 |
| 64 | 2 | 0.1 | 0.1 |
| 65 | 9 | 0.5 | 0.5 |
| 66 | 1 | 0.1 | 0.1 |
| 67 | 3 | 0.2 | 0.2 |
| 68 | 5 | 0.3 | 0.3 |
| 69 | 3 | 0.2 | 0.2 |
| 7 | 2 | 0.1 | 0.1 |
| 70 | 2 | 0.1 | 0.1 |
| 71 | 3 | 0.2 | 0.2 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 3 | 0.2 | 0.2 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 1 | 0.1 | 0.1 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 2 | 0.1 | 0.1 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 5 | 0.3 | 0.3 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 1553 | 88.5 | 88.5 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1536 | 87.6 | 90.8 |
| Yes | 156 | 8.9 | 9.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 62 | 3.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 20 | 1.1 | 1.1 |
| 10 | 1 | 0.1 | 0.1 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 2 | 0.1 | 0.1 |
| 15 | 1 | 0.1 | 0.1 |
| 16 | 4 | 0.2 | 0.2 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 2 | 0.1 | 0.1 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.1 | 0.1 |
| 20 | 3 | 0.2 | 0.2 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 2 | 0.1 | 0.1 |
| 23 | 2 | 0.1 | 0.1 |
| 24 | 2 | 0.1 | 0.1 |
| 25 | 4 | 0.2 | 0.2 |
| 27 | 2 | 0.1 | 0.1 |
| 28 | 2 | 0.1 | 0.1 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 6 | 0.3 | 0.3 |
| 32 | 2 | 0.1 | 0.1 |
| 34 | 1 | 0.1 | 0.1 |
| 35 | 8 | 0.5 | 0.5 |
| 36 | 2 | 0.1 | 0.1 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 2 | 0.1 | 0.1 |
| 40 | 12 | 0.7 | 0.7 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 1 | 0.1 | 0.1 |
| 45 | 8 | 0.5 | 0.5 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 3 | 0.2 | 0.2 |
| 48 | 4 | 0.2 | 0.2 |
| 49 | 1 | 0.1 | 0.1 |
| 50 | 6 | 0.3 | 0.3 |
| 52 | 1 | 0.1 | 0.1 |
| 53 | 1 | 0.1 | 0.1 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 3 | 0.2 | 0.2 |
| 56 | 2 | 0.1 | 0.1 |
| 57 | 2 | 0.1 | 0.1 |
| 58 | 2 | 0.1 | 0.1 |
| 59 | 1 | 0.1 | 0.1 |
| 60 | 2 | 0.1 | 0.1 |
| 61 | 1 | 0.1 | 0.1 |
| 62 | 7 | 0.4 | 0.4 |
| 63 | 3 | 0.2 | 0.2 |
| 64 | 2 | 0.1 | 0.1 |
| 65 | 2 | 0.1 | 0.1 |
| 66 | 1 | 0.1 | 0.1 |
| 67 | 4 | 0.2 | 0.2 |
| 68 | 1 | 0.1 | 0.1 |
| 69 | 2 | 0.1 | 0.1 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 1 | 0.1 | 0.1 |
| 71 | 1 | 0.1 | 0.1 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 1 | 0.1 | 0.1 |
| 76 | 1 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 1 | 0.1 | 0.1 |
| 94 | 1 | 0.1 | 0.1 |
| “NA” | 1604 | 91.4 | 91.4 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1629 | 92.9 | 96.4 |
| Yes | 60 | 3.4 | 3.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 65 | 3.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.1 | 0.1 |
| 22 | 0 | 0.0 | 0.0 |
| 30 | 1 | 0.1 | 0.1 |
| 32 | 1 | 0.1 | 0.1 |
| 33 | 1 | 0.1 | 0.1 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.1 | 0.1 |
| 37 | 1 | 0.1 | 0.1 |
| 39 | 1 | 0.1 | 0.1 |
| 40 | 6 | 0.3 | 0.3 |
| 41 | 0 | 0.0 | 0.0 |
| 44 | 2 | 0.1 | 0.1 |
| 45 | 1 | 0.1 | 0.1 |
| 46 | 1 | 0.1 | 0.1 |
| 48 | 1 | 0.1 | 0.1 |
| 50 | 2 | 0.1 | 0.1 |
| 51 | 1 | 0.1 | 0.1 |
| 52 | 2 | 0.1 | 0.1 |
| 53 | 1 | 0.1 | 0.1 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 3 | 0.2 | 0.2 |
| 56 | 2 | 0.1 | 0.1 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 2 | 0.1 | 0.1 |
| 59 | 1 | 0.1 | 0.1 |
| 60 | 4 | 0.2 | 0.2 |
| 62 | 1 | 0.1 | 0.1 |
| 63 | 2 | 0.1 | 0.1 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 0.1 | 0.1 |
| 66 | 1 | 0.1 | 0.1 |
| 67 | 0 | 0.0 | 0.0 |
| 69 | 2 | 0.1 | 0.1 |
| 70 | 1 | 0.1 | 0.1 |
| 71 | 1 | 0.1 | 0.1 |
| 74 | 1 | 0.1 | 0.1 |
| 75 | 1 | 0.1 | 0.1 |
| 76 | 1 | 0.1 | 0.1 |
| 79 | 0 | 0.0 | 0.0 |
| 85 | 1 | 0.1 | 0.1 |
| “NA” | 1703 | 97.1 | 97.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1173 | 66.9 | 68.6 |
| Yes | 534 | 30.4 | 31.2 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 44 | 2.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 0.3 | 0.3 |
| 10 | 1 | 0.1 | 0.1 |
| 12 | 1 | 0.1 | 0.1 |
| 13 | 2 | 0.1 | 0.1 |
| 14 | 1 | 0.1 | 0.1 |
| 15 | 2 | 0.1 | 0.1 |
| 16 | 1 | 0.1 | 0.1 |
| 17 | 1 | 0.1 | 0.1 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.1 | 0.1 |
| 20 | 1 | 0.1 | 0.1 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.1 | 0.1 |
| 27 | 1 | 0.1 | 0.1 |
| 28 | 1 | 0.1 | 0.1 |
| 29 | 1 | 0.1 | 0.1 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 7 | 0.4 | 0.4 |
| 31 | 1 | 0.1 | 0.1 |
| 32 | 1 | 0.1 | 0.1 |
| 34 | 1 | 0.1 | 0.1 |
| 35 | 13 | 0.7 | 0.7 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 3 | 0.2 | 0.2 |
| 38 | 2 | 0.1 | 0.1 |
| 39 | 3 | 0.2 | 0.2 |
| 40 | 23 | 1.3 | 1.3 |
| 41 | 2 | 0.1 | 0.1 |
| 42 | 5 | 0.3 | 0.3 |
| 43 | 7 | 0.4 | 0.4 |
| 44 | 6 | 0.3 | 0.3 |
| 45 | 26 | 1.5 | 1.5 |
| 46 | 6 | 0.3 | 0.3 |
| 47 | 7 | 0.4 | 0.4 |
| 48 | 6 | 0.3 | 0.3 |
| 49 | 3 | 0.2 | 0.2 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 43 | 2.5 | 2.5 |
| 51 | 5 | 0.3 | 0.3 |
| 52 | 8 | 0.5 | 0.5 |
| 53 | 11 | 0.6 | 0.6 |
| 54 | 16 | 0.9 | 0.9 |
| 55 | 36 | 2.1 | 2.1 |
| 56 | 13 | 0.7 | 0.7 |
| 57 | 8 | 0.5 | 0.5 |
| 58 | 15 | 0.9 | 0.9 |
| 59 | 15 | 0.9 | 0.9 |
| 60 | 34 | 1.9 | 1.9 |
| 61 | 13 | 0.7 | 0.7 |
| 62 | 17 | 1.0 | 1.0 |
| 63 | 9 | 0.5 | 0.5 |
| 64 | 10 | 0.6 | 0.6 |
| 65 | 18 | 1.0 | 1.0 |
| 66 | 5 | 0.3 | 0.3 |
| 67 | 4 | 0.2 | 0.2 |
| 68 | 6 | 0.3 | 0.3 |
| 69 | 7 | 0.4 | 0.4 |
| 70 | 12 | 0.7 | 0.7 |
| 71 | 4 | 0.2 | 0.2 |
| 72 | 3 | 0.2 | 0.2 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 2 | 0.1 | 0.1 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 0 | 0.0 | 0.0 |
| 78 | 1 | 0.1 | 0.1 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 1 | 0.1 | 0.1 |
| “NA” | 1292 | 73.7 | 73.7 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1597 | 91.0 | 93.7 |
| Yes | 107 | 6.1 | 6.3 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 49 | 2.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 1 | 0.1 | 0.1 |
| 16 | 1 | 0.1 | 0.1 |
| 17 | 1 | 0.1 | 0.1 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 1 | 0.1 | 0.1 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 3 | 0.2 | 0.2 |
| 42 | 1 | 0.1 | 0.1 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.1 | 0.1 |
| 46 | 1 | 0.1 | 0.1 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 4 | 0.2 | 0.2 |
| 51 | 2 | 0.1 | 0.1 |
| 52 | 1 | 0.1 | 0.1 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 5 | 0.3 | 0.3 |
| 55 | 5 | 0.3 | 0.3 |
| 56 | 6 | 0.3 | 0.3 |
| 57 | 1 | 0.1 | 0.1 |
| 58 | 1 | 0.1 | 0.1 |
| 59 | 2 | 0.1 | 0.1 |
| 60 | 1 | 0.1 | 0.1 |
| 61 | 3 | 0.2 | 0.2 |
| 62 | 6 | 0.3 | 0.3 |
| 63 | 1 | 0.1 | 0.1 |
| 64 | 4 | 0.2 | 0.2 |
| 65 | 7 | 0.4 | 0.4 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 4 | 0.2 | 0.2 |
| 68 | 1 | 0.1 | 0.1 |
| 69 | 3 | 0.2 | 0.2 |
| 7 | 1 | 0.1 | 0.1 |
| 70 | 4 | 0.2 | 0.2 |
| 71 | 1 | 0.1 | 0.1 |
| 72 | 1 | 0.1 | 0.1 |
| 74 | 1 | 0.1 | 0.1 |
| 75 | 3 | 0.2 | 0.2 |
| 76 | 1 | 0.1 | 0.1 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 1671 | 95.3 | 95.3 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1666 | 95.0 | 98.6 |
| Yes | 24 | 1.4 | 1.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 64 | 3.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.1 | 0.1 |
| 40 | 1 | 0.1 | 0.1 |
| 42 | 1 | 0.1 | 0.1 |
| 45 | 2 | 0.1 | 0.1 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 1 | 0.1 | 0.1 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 1 | 0.1 | 0.1 |
| 55 | 2 | 0.1 | 0.1 |
| 58 | 0 | 0.0 | 0.0 |
| 60 | 3 | 0.2 | 0.2 |
| 61 | 0 | 0.0 | 0.0 |
| 63 | 1 | 0.1 | 0.1 |
| 64 | 1 | 0.1 | 0.1 |
| 65 | 2 | 0.1 | 0.1 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 1 | 0.1 | 0.1 |
| 74 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| “NA” | 1737 | 99.0 | 99.0 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1495 | 85.2 | 88.1 |
| Yes | 202 | 11.5 | 11.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 57 | 3.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 1 | 0.1 | 0.1 |
| 20 | 2 | 0.1 | 0.1 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 1 | 0.1 | 0.1 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.1 | 0.1 |
| 25 | 3 | 0.2 | 0.2 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 4 | 0.2 | 0.2 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 1 | 0.1 | 0.1 |
| 35 | 2 | 0.1 | 0.1 |
| 36 | 1 | 0.1 | 0.1 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.1 | 0.1 |
| 4 | 1 | 0.1 | 0.1 |
| 40 | 9 | 0.5 | 0.5 |
| 41 | 2 | 0.1 | 0.1 |
| 42 | 2 | 0.1 | 0.1 |
| 43 | 3 | 0.2 | 0.2 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 5 | 0.3 | 0.3 |
| 46 | 1 | 0.1 | 0.1 |
| 47 | 4 | 0.2 | 0.2 |
| 48 | 1 | 0.1 | 0.1 |
| 49 | 1 | 0.1 | 0.1 |
| 50 | 17 | 1.0 | 1.0 |
| 51 | 3 | 0.2 | 0.2 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 2 | 0.1 | 0.1 |
| 54 | 1 | 0.1 | 0.1 |
| 55 | 18 | 1.0 | 1.0 |
| 56 | 3 | 0.2 | 0.2 |
| 57 | 2 | 0.1 | 0.1 |
| 58 | 7 | 0.4 | 0.4 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 18 | 1.0 | 1.0 |
| 61 | 3 | 0.2 | 0.2 |
| 62 | 4 | 0.2 | 0.2 |
| 63 | 2 | 0.1 | 0.1 |
| 64 | 2 | 0.1 | 0.1 |
| 65 | 12 | 0.7 | 0.7 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 5 | 0.3 | 0.3 |
| 68 | 4 | 0.2 | 0.2 |
| 69 | 2 | 0.1 | 0.1 |
| 7 | 1 | 0.1 | 0.1 |
| 70 | 5 | 0.3 | 0.3 |
| 71 | 2 | 0.1 | 0.1 |
| 72 | 1 | 0.1 | 0.1 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 1589 | 90.6 | 90.6 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1677 | 95.6 | 98.5 |
| Yes | 25 | 1.4 | 1.5 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 51 | 2.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 1 | 0.1 | 0.1 |
| 29 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 62 | 1 | 0.1 | 0.1 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 1 | 0.1 | 0.1 |
| 65 | 1 | 0.1 | 0.1 |
| 66 | 1 | 0.1 | 0.1 |
| 67 | 1 | 0.1 | 0.1 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 5 | 0.3 | 0.3 |
| 72 | 1 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.1 | 0.1 |
| 75 | 1 | 0.1 | 0.1 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 1738 | 99.1 | 99.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1471 | 83.9 | 86.8 |
| Yes | 223 | 12.7 | 13.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 59 | 3.4 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.1 | 0.1 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 1 | 0.1 | 0.1 |
| 18 | 1 | 0.1 | 0.1 |
| 19 | 2 | 0.1 | 0.1 |
| 20 | 1 | 0.1 | 0.1 |
| 21 | 3 | 0.2 | 0.2 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 0.1 | 0.1 |
| 26 | 2 | 0.1 | 0.1 |
| 28 | 3 | 0.2 | 0.2 |
| 29 | 1 | 0.1 | 0.1 |
| 30 | 1 | 0.1 | 0.1 |
| 32 | 3 | 0.2 | 0.2 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 4 | 0.2 | 0.2 |
| 36 | 3 | 0.2 | 0.2 |
| 37 | 3 | 0.2 | 0.2 |
| 38 | 1 | 0.1 | 0.1 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 1 | 0.1 | 0.1 |
| 40 | 8 | 0.5 | 0.5 |
| 41 | 1 | 0.1 | 0.1 |
| 42 | 1 | 0.1 | 0.1 |
| 43 | 3 | 0.2 | 0.2 |
| 44 | 1 | 0.1 | 0.1 |
| 45 | 7 | 0.4 | 0.4 |
| 46 | 2 | 0.1 | 0.1 |
| 47 | 4 | 0.2 | 0.2 |
| 48 | 4 | 0.2 | 0.2 |
| 49 | 5 | 0.3 | 0.3 |
| 50 | 14 | 0.8 | 0.8 |
| 51 | 1 | 0.1 | 0.1 |
| 52 | 4 | 0.2 | 0.2 |
| 53 | 3 | 0.2 | 0.2 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 12 | 0.7 | 0.7 |
| 56 | 5 | 0.3 | 0.3 |
| 57 | 3 | 0.2 | 0.2 |
| 58 | 6 | 0.3 | 0.3 |
| 59 | 4 | 0.2 | 0.2 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 8 | 0.5 | 0.5 |
| 61 | 3 | 0.2 | 0.2 |
| 62 | 3 | 0.2 | 0.2 |
| 63 | 3 | 0.2 | 0.2 |
| 64 | 3 | 0.2 | 0.2 |
| 65 | 8 | 0.5 | 0.5 |
| 66 | 3 | 0.2 | 0.2 |
| 67 | 3 | 0.2 | 0.2 |
| 68 | 5 | 0.3 | 0.3 |
| 69 | 1 | 0.1 | 0.1 |
| 7 | 1 | 0.1 | 0.1 |
| 70 | 2 | 0.1 | 0.1 |
| 72 | 1 | 0.1 | 0.1 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 1 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| 91 | 1 | 0.1 | 0.1 |
| 96 | 1 | 0.1 | 0.1 |
| 98 | 1 | 0.1 | 0.1 |
| “NA” | 1582 | 90.2 | 90.2 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1675 | 95.5 | 98.8 |
| Yes | 20 | 1.1 | 1.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 59 | 3.4 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 21 | 1.2 | 1.2 |
| 25 | 1 | 0.1 | 0.1 |
| 30 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 36 | 1 | 0.1 | 0.1 |
| 38 | 1 | 0.1 | 0.1 |
| 39 | 1 | 0.1 | 0.1 |
| 40 | 2 | 0.1 | 0.1 |
| 45 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 1 | 0.1 | 0.1 |
| 50 | 1 | 0.1 | 0.1 |
| 51 | 1 | 0.1 | 0.1 |
| 55 | 0 | 0.0 | 0.0 |
| 59 | 1 | 0.1 | 0.1 |
| 60 | 1 | 0.1 | 0.1 |
| 63 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 90 | 1 | 0.1 | 0.1 |
| “NA” | 1721 | 98.1 | 98.1 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1564 | 89.2 | 92.9 |
| Yes | 120 | 6.8 | 7.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 70 | 4.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 1 | 0.1 | 0.1 |
| 18 | 1 | 0.1 | 0.1 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 1 | 0.1 | 0.1 |
| 30 | 1 | 0.1 | 0.1 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 1 | 0.1 | 0.1 |
| 40 | 1 | 0.1 | 0.1 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 1 | 0.1 | 0.1 |
| 43 | 1 | 0.1 | 0.1 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 1 | 0.1 | 0.1 |
| 47 | 1 | 0.1 | 0.1 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 4 | 0.2 | 0.2 |
| 50 | 1 | 0.1 | 0.1 |
| 51 | 1 | 0.1 | 0.1 |
| 52 | 1 | 0.1 | 0.1 |
| 54 | 4 | 0.2 | 0.2 |
| 55 | 4 | 0.2 | 0.2 |
| 56 | 5 | 0.3 | 0.3 |
| 57 | 2 | 0.1 | 0.1 |
| 58 | 7 | 0.4 | 0.4 |
| 59 | 2 | 0.1 | 0.1 |
| 60 | 8 | 0.5 | 0.5 |
| 61 | 6 | 0.3 | 0.3 |
| 62 | 5 | 0.3 | 0.3 |
| 63 | 4 | 0.2 | 0.2 |
| 64 | 4 | 0.2 | 0.2 |
| 65 | 3 | 0.2 | 0.2 |
| 66 | 2 | 0.1 | 0.1 |
| 67 | 3 | 0.2 | 0.2 |
| 68 | 3 | 0.2 | 0.2 |
| 69 | 3 | 0.2 | 0.2 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 5 | 0.3 | 0.3 |
| 71 | 1 | 0.1 | 0.1 |
| 72 | 2 | 0.1 | 0.1 |
| 73 | 1 | 0.1 | 0.1 |
| 74 | 5 | 0.3 | 0.3 |
| 75 | 2 | 0.1 | 0.1 |
| 76 | 1 | 0.1 | 0.1 |
| 77 | 1 | 0.1 | 0.1 |
| 78 | 1 | 0.1 | 0.1 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 1653 | 94.2 | 94.2 |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 6.2 | 6.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 1 | 6.2 | 6.2 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| “NA” | 13 | 81.2 | 81.2 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 81.2 |
| Yes | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 6.2 | 6.2 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 6.2 | 6.2 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 13 | 81.2 | 81.2 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 86.7 |
| Yes | 2 | 12.5 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 6.2 | 6.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 6.2 | 6.2 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| “NA” | 14 | 87.5 | 87.5 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 4 | 25 | 25 |
| Yes | 12 | 75 | 75 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| .35 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 1 | 6.2 | 6.2 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 1 | 6.2 | 6.2 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 2 | 12.5 | 12.5 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 1 | 6.2 | 6.2 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 1 | 6.2 | 6.2 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 6.2 | 6.2 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 6.2 | 6.2 |
| 66 | 1 | 6.2 | 6.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 89 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 6 | 37.5 | 37.5 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 93.3 |
| Yes | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| * | 0 | 0.0 | 0.0 |
| ** | 0 | 0.0 | 0.0 |
| 0 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 6.2 | 6.2 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 82 | 0 | 0.0 | 0.0 |
| 84 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 15 | 93.8 | 93.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 7 | 43.8 | 46.7 |
| Yes | 8 | 50.0 | 53.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 1 | 6.2 | 6.2 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 1 | 6.2 | 6.2 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 1 | 6.2 | 6.2 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 6.2 | 6.2 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 2 | 12.5 | 12.5 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 6.2 | 6.2 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 1 | 6.2 | 6.2 |
| 66 | 1 | 6.2 | 6.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 86 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 92 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| 99 | 0 | 0.0 | 0.0 |
| “NA” | 7 | 43.8 | 43.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 11 | 68.8 | 73.3 |
| Yes | 4 | 25.0 | 26.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 06 | 0 | 0.0 | 0.0 |
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 11 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 25 | 1 | 6.2 | 6.2 |
| 26 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 1 | 6.2 | 6.2 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 1 | 6.2 | 6.2 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 93 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 12 | 75.0 | 75.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 92.9 |
| Yes | 1 | 6.2 | 7.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 6.2 | 6.2 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 9 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| “NA” | 15 | 93.8 | 93.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 100 |
| Yes | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| 15 | 0 | 0 | 0 |
| 2 | 0 | 0 | 0 |
| 22 | 0 | 0 | 0 |
| 30 | 0 | 0 | 0 |
| 32 | 0 | 0 | 0 |
| 33 | 0 | 0 | 0 |
| 34 | 0 | 0 | 0 |
| 35 | 0 | 0 | 0 |
| 37 | 0 | 0 | 0 |
| 39 | 0 | 0 | 0 |
| 40 | 0 | 0 | 0 |
| 41 | 0 | 0 | 0 |
| 44 | 0 | 0 | 0 |
| 45 | 0 | 0 | 0 |
| 46 | 0 | 0 | 0 |
| 48 | 0 | 0 | 0 |
| 50 | 0 | 0 | 0 |
| 51 | 0 | 0 | 0 |
| 52 | 0 | 0 | 0 |
| 53 | 0 | 0 | 0 |
| 54 | 0 | 0 | 0 |
| 55 | 0 | 0 | 0 |
| 56 | 0 | 0 | 0 |
| 57 | 0 | 0 | 0 |
| 58 | 0 | 0 | 0 |
| 59 | 0 | 0 | 0 |
| 60 | 0 | 0 | 0 |
| 62 | 0 | 0 | 0 |
| 63 | 0 | 0 | 0 |
| 64 | 0 | 0 | 0 |
| 65 | 0 | 0 | 0 |
| 66 | 0 | 0 | 0 |
| 67 | 0 | 0 | 0 |
| 69 | 0 | 0 | 0 |
| 70 | 0 | 0 | 0 |
| 71 | 0 | 0 | 0 |
| 74 | 0 | 0 | 0 |
| 75 | 0 | 0 | 0 |
| 76 | 0 | 0 | 0 |
| 79 | 0 | 0 | 0 |
| 85 | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 7 | 43.8 | 43.8 |
| Yes | 9 | 56.2 | 56.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 13 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 27 | 0 | 0.0 | 0.0 |
| 28 | 1 | 6.2 | 6.2 |
| 29 | 0 | 0.0 | 0.0 |
| 3 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 31 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 1 | 6.2 | 6.2 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 1 | 6.2 | 6.2 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 1 | 6.2 | 6.2 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 6.2 | 6.2 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 1 | 6.2 | 6.2 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 1 | 6.2 | 6.2 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 1 | 6.2 | 6.2 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 81 | 0 | 0.0 | 0.0 |
| 94 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| 97 | 0 | 0.0 | 0.0 |
| “NA” | 7 | 43.8 | 43.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 81.2 |
| Yes | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 11 | 0 | 0.0 | 0.0 |
| 15 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 5 | 0 | 0.0 | 0.0 |
| 50 | 1 | 6.2 | 6.2 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 1 | 6.2 | 6.2 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| 83 | 0 | 0.0 | 0.0 |
| 95 | 0 | 0.0 | 0.0 |
| “NA” | 14 | 87.5 | 87.5 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 15 | 93.8 | 93.8 |
| Yes | 1 | 6.2 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 18 | 0 | 0 | 0 |
| 21 | 0 | 0 | 0 |
| 39 | 0 | 0 | 0 |
| 40 | 0 | 0 | 0 |
| 42 | 0 | 0 | 0 |
| 45 | 0 | 0 | 0 |
| 47 | 0 | 0 | 0 |
| 48 | 0 | 0 | 0 |
| 49 | 0 | 0 | 0 |
| 50 | 0 | 0 | 0 |
| 51 | 0 | 0 | 0 |
| 53 | 0 | 0 | 0 |
| 54 | 0 | 0 | 0 |
| 55 | 0 | 0 | 0 |
| 58 | 0 | 0 | 0 |
| 60 | 0 | 0 | 0 |
| 61 | 0 | 0 | 0 |
| 63 | 0 | 0 | 0 |
| 64 | 0 | 0 | 0 |
| 65 | 0 | 0 | 0 |
| 66 | 0 | 0 | 0 |
| 67 | 0 | 0 | 0 |
| 68 | 0 | 0 | 0 |
| 69 | 0 | 0 | 0 |
| 74 | 0 | 0 | 0 |
| 77 | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 10 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 23 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 1 | 6.2 | 6.2 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 80 | 0 | 0.0 | 0.0 |
| “NA” | 15 | 93.8 | 93.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 16 | 100 | 100 |
| Yes | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0 | 0 |
| 29 | 0 | 0 | 0 |
| 53 | 0 | 0 | 0 |
| 57 | 0 | 0 | 0 |
| 60 | 0 | 0 | 0 |
| 62 | 0 | 0 | 0 |
| 63 | 0 | 0 | 0 |
| 64 | 0 | 0 | 0 |
| 65 | 0 | 0 | 0 |
| 66 | 0 | 0 | 0 |
| 67 | 0 | 0 | 0 |
| 69 | 0 | 0 | 0 |
| 70 | 0 | 0 | 0 |
| 72 | 0 | 0 | 0 |
| 73 | 0 | 0 | 0 |
| 74 | 0 | 0 | 0 |
| 75 | 0 | 0 | 0 |
| 80 | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 1 | 0 | 0.0 | 0.0 |
| 14 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 17 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 21 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 25 | 0 | 0.0 | 0.0 |
| 26 | 0 | 0.0 | 0.0 |
| 28 | 0 | 0.0 | 0.0 |
| 29 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 32 | 0 | 0.0 | 0.0 |
| 33 | 0 | 0.0 | 0.0 |
| 34 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 37 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 4 | 0 | 0.0 | 0.0 |
| 40 | 1 | 6.2 | 6.2 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 46 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 53 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 6 | 0 | 0.0 | 0.0 |
| 60 | 0 | 0.0 | 0.0 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 8 | 0 | 0.0 | 0.0 |
| 91 | 0 | 0.0 | 0.0 |
| 96 | 0 | 0.0 | 0.0 |
| 98 | 0 | 0.0 | 0.0 |
| “NA” | 15 | 93.8 | 93.8 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 16 | 100 | 100 |
| Yes | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| 0 | 0 | 0 | 0 |
| 25 | 0 | 0 | 0 |
| 30 | 0 | 0 | 0 |
| 33 | 0 | 0 | 0 |
| 36 | 0 | 0 | 0 |
| 38 | 0 | 0 | 0 |
| 39 | 0 | 0 | 0 |
| 40 | 0 | 0 | 0 |
| 45 | 0 | 0 | 0 |
| 48 | 0 | 0 | 0 |
| 49 | 0 | 0 | 0 |
| 50 | 0 | 0 | 0 |
| 51 | 0 | 0 | 0 |
| 55 | 0 | 0 | 0 |
| 59 | 0 | 0 | 0 |
| 60 | 0 | 0 | 0 |
| 63 | 0 | 0 | 0 |
| 65 | 0 | 0 | 0 |
| 9 | 0 | 0 | 0 |
| 90 | 0 | 0 | 0 |
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 15 | 93.8 | 93.8 |
| Yes | 1 | 6.2 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| 10 | 0 | 0.0 | 0.0 |
| 12 | 0 | 0.0 | 0.0 |
| 16 | 0 | 0.0 | 0.0 |
| 18 | 0 | 0.0 | 0.0 |
| 19 | 0 | 0.0 | 0.0 |
| 2 | 0 | 0.0 | 0.0 |
| 20 | 0 | 0.0 | 0.0 |
| 22 | 0 | 0.0 | 0.0 |
| 24 | 0 | 0.0 | 0.0 |
| 30 | 0 | 0.0 | 0.0 |
| 35 | 0 | 0.0 | 0.0 |
| 36 | 0 | 0.0 | 0.0 |
| 38 | 0 | 0.0 | 0.0 |
| 39 | 0 | 0.0 | 0.0 |
| 40 | 0 | 0.0 | 0.0 |
| 41 | 0 | 0.0 | 0.0 |
| 42 | 0 | 0.0 | 0.0 |
| 43 | 0 | 0.0 | 0.0 |
| 44 | 0 | 0.0 | 0.0 |
| 45 | 0 | 0.0 | 0.0 |
| 47 | 0 | 0.0 | 0.0 |
| 48 | 0 | 0.0 | 0.0 |
| 49 | 0 | 0.0 | 0.0 |
| 50 | 0 | 0.0 | 0.0 |
| 51 | 0 | 0.0 | 0.0 |
| 52 | 0 | 0.0 | 0.0 |
| 54 | 0 | 0.0 | 0.0 |
| 55 | 0 | 0.0 | 0.0 |
| 56 | 0 | 0.0 | 0.0 |
| 57 | 0 | 0.0 | 0.0 |
| 58 | 0 | 0.0 | 0.0 |
| 59 | 0 | 0.0 | 0.0 |
| 60 | 1 | 6.2 | 6.2 |
| 61 | 0 | 0.0 | 0.0 |
| 62 | 0 | 0.0 | 0.0 |
| 63 | 0 | 0.0 | 0.0 |
| 64 | 0 | 0.0 | 0.0 |
| 65 | 0 | 0.0 | 0.0 |
| 66 | 0 | 0.0 | 0.0 |
| 67 | 0 | 0.0 | 0.0 |
| 68 | 0 | 0.0 | 0.0 |
| 69 | 0 | 0.0 | 0.0 |
| 7 | 0 | 0.0 | 0.0 |
| 70 | 0 | 0.0 | 0.0 |
| 71 | 0 | 0.0 | 0.0 |
| 72 | 0 | 0.0 | 0.0 |
| 73 | 0 | 0.0 | 0.0 |
| 74 | 0 | 0.0 | 0.0 |
| 75 | 0 | 0.0 | 0.0 |
| 76 | 0 | 0.0 | 0.0 |
| 77 | 0 | 0.0 | 0.0 |
| 78 | 0 | 0.0 | 0.0 |
| 79 | 0 | 0.0 | 0.0 |
| “NA” | 15 | 93.8 | 93.8 |
| Total | 16 | 100.0 | 100.0 |
b5 <- as.factor(d[,"b5"])
levels(b5) <- list(Community_center_free_clinic="1",
Hospital_urgent_care_clinic="2",
Private_Dr_office="3",
ER="4",
VA="5",
Other="6",
Scantron_Error="*")
b5 <- ordered(b5, c("Community_center_free_clinic", "Hospital_urgent_care_clinic", "Private_Dr_office", "ER","VA","Other","Scantron_Error"))
new.d <- data.frame(new.d, b5)
new.d <- apply_labels(new.d, b5 = "routine medical care")
temp.d <- data.frame (new.d, b5)
result<-questionr::freq(temp.d$b5 ,total = TRUE)
kable(result, format = "simple", align = 'l')
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 246 | 6.9 | 7.2 |
| Hospital_urgent_care_clinic | 263 | 7.4 | 7.7 |
| Private_Dr_office | 2277 | 64.0 | 66.7 |
| ER | 24 | 0.7 | 0.7 |
| VA | 361 | 10.1 | 10.6 |
| Other | 63 | 1.8 | 1.8 |
| Scantron_Error | 178 | 5.0 | 5.2 |
| NA | 145 | 4.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 21 | 6.5 | 6.6 |
| Hospital_urgent_care_clinic | 20 | 6.2 | 6.3 |
| Private_Dr_office | 242 | 75.4 | 76.6 |
| ER | 2 | 0.6 | 0.6 |
| VA | 13 | 4.0 | 4.1 |
| Other | 6 | 1.9 | 1.9 |
| Scantron_Error | 12 | 3.7 | 3.8 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 16 | 7.6 | 8.0 |
| Hospital_urgent_care_clinic | 22 | 10.5 | 10.9 |
| Private_Dr_office | 145 | 69.0 | 72.1 |
| ER | 1 | 0.5 | 0.5 |
| VA | 7 | 3.3 | 3.5 |
| Other | 3 | 1.4 | 1.5 |
| Scantron_Error | 7 | 3.3 | 3.5 |
| NA | 9 | 4.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 23 | 7.3 | 7.7 |
| Hospital_urgent_care_clinic | 27 | 8.6 | 9.0 |
| Private_Dr_office | 216 | 68.6 | 72.2 |
| ER | 2 | 0.6 | 0.7 |
| VA | 18 | 5.7 | 6.0 |
| Other | 7 | 2.2 | 2.3 |
| Scantron_Error | 6 | 1.9 | 2.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 25 | 7.0 | 7.4 |
| Hospital_urgent_care_clinic | 46 | 12.9 | 13.6 |
| Private_Dr_office | 231 | 64.9 | 68.1 |
| ER | 2 | 0.6 | 0.6 |
| VA | 10 | 2.8 | 2.9 |
| Other | 9 | 2.5 | 2.7 |
| Scantron_Error | 16 | 4.5 | 4.7 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 59 | 10.1 | 10.5 |
| Hospital_urgent_care_clinic | 58 | 9.9 | 10.4 |
| Private_Dr_office | 315 | 53.8 | 56.2 |
| ER | 4 | 0.7 | 0.7 |
| VA | 76 | 13.0 | 13.6 |
| Other | 6 | 1.0 | 1.1 |
| Scantron_Error | 42 | 7.2 | 7.5 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 101 | 5.8 | 6.0 |
| Hospital_urgent_care_clinic | 87 | 5.0 | 5.2 |
| Private_Dr_office | 1119 | 63.8 | 66.5 |
| ER | 13 | 0.7 | 0.8 |
| VA | 237 | 13.5 | 14.1 |
| Other | 32 | 1.8 | 1.9 |
| Scantron_Error | 94 | 5.4 | 5.6 |
| NA | 71 | 4.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Community_center_free_clinic | 1 | 6.2 | 7.1 |
| Hospital_urgent_care_clinic | 3 | 18.8 | 21.4 |
| Private_Dr_office | 9 | 56.2 | 64.3 |
| ER | 0 | 0.0 | 0.0 |
| VA | 0 | 0.0 | 0.0 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 1 | 6.2 | 7.1 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100.0 |
c1 <- as.factor(d[,"c1"])
levels(c1) <- list(Less_than_1_year="1",
years_1_5="2",
years_6_10="3",
years_11_15="4",
years_16_20="5",
years_21_more="6",
Scantron_Error="*")
c1 <- ordered(c1, c("Less_than_1_year", "years_1_5", "years_6_10", "years_11_15","years_16_20","years_21_more","Scantron_Error"))
new.d <- data.frame(new.d, c1)
new.d <- apply_labels(new.d, c1 = "living period")
temp.d <- data.frame (new.d, c1)
result<-questionr::freq(temp.d$c1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l')
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 137 | 3.9 | 3.9 | 3.9 | 3.9 |
| years_1_5 | 610 | 17.1 | 17.4 | 21.0 | 21.3 |
| years_6_10 | 478 | 13.4 | 13.6 | 34.4 | 34.9 |
| years_11_15 | 413 | 11.6 | 11.8 | 46.1 | 46.7 |
| years_16_20 | 473 | 13.3 | 13.5 | 59.3 | 60.2 |
| years_21_more | 1392 | 39.1 | 39.7 | 98.5 | 99.9 |
| Scantron_Error | 5 | 0.1 | 0.1 | 98.6 | 100.0 |
| NA | 49 | 1.4 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 18 | 5.6 | 5.6 | 5.6 | 5.6 |
| years_1_5 | 67 | 20.9 | 20.9 | 26.5 | 26.5 |
| years_6_10 | 39 | 12.1 | 12.1 | 38.6 | 38.6 |
| years_11_15 | 26 | 8.1 | 8.1 | 46.7 | 46.7 |
| years_16_20 | 40 | 12.5 | 12.5 | 59.2 | 59.2 |
| years_21_more | 131 | 40.8 | 40.8 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 12 | 5.7 | 5.8 | 5.7 | 5.8 |
| years_1_5 | 36 | 17.1 | 17.5 | 22.9 | 23.3 |
| years_6_10 | 29 | 13.8 | 14.1 | 36.7 | 37.4 |
| years_11_15 | 25 | 11.9 | 12.1 | 48.6 | 49.5 |
| years_16_20 | 21 | 10.0 | 10.2 | 58.6 | 59.7 |
| years_21_more | 82 | 39.0 | 39.8 | 97.6 | 99.5 |
| Scantron_Error | 1 | 0.5 | 0.5 | 98.1 | 100.0 |
| NA | 4 | 1.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 11 | 3.5 | 3.6 | 3.5 | 3.6 |
| years_1_5 | 74 | 23.5 | 24.1 | 27.0 | 27.7 |
| years_6_10 | 53 | 16.8 | 17.3 | 43.8 | 45.0 |
| years_11_15 | 43 | 13.7 | 14.0 | 57.5 | 59.0 |
| years_16_20 | 46 | 14.6 | 15.0 | 72.1 | 73.9 |
| years_21_more | 79 | 25.1 | 25.7 | 97.1 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 97.5 | 100.0 |
| NA | 8 | 2.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 18 | 5.1 | 5.1 | 5.1 | 5.1 |
| years_1_5 | 67 | 18.8 | 18.9 | 23.9 | 23.9 |
| years_6_10 | 57 | 16.0 | 16.1 | 39.9 | 40.0 |
| years_11_15 | 48 | 13.5 | 13.5 | 53.4 | 53.5 |
| years_16_20 | 38 | 10.7 | 10.7 | 64.0 | 64.2 |
| years_21_more | 126 | 35.4 | 35.5 | 99.4 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 16 | 2.7 | 2.8 | 2.7 | 2.8 |
| years_1_5 | 75 | 12.8 | 13.0 | 15.6 | 15.8 |
| years_6_10 | 69 | 11.8 | 12.0 | 27.4 | 27.7 |
| years_11_15 | 72 | 12.3 | 12.5 | 39.7 | 40.2 |
| years_16_20 | 60 | 10.3 | 10.4 | 49.9 | 50.6 |
| years_21_more | 284 | 48.5 | 49.2 | 98.5 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 98.6 | 100.0 |
| NA | 8 | 1.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 62 | 3.5 | 3.6 | 3.5 | 3.6 |
| years_1_5 | 289 | 16.5 | 16.7 | 20.0 | 20.3 |
| years_6_10 | 227 | 12.9 | 13.2 | 33.0 | 33.5 |
| years_11_15 | 196 | 11.2 | 11.4 | 44.1 | 44.8 |
| years_16_20 | 266 | 15.2 | 15.4 | 59.3 | 60.3 |
| years_21_more | 685 | 39.1 | 39.7 | 98.3 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 98.4 | 100.0 |
| NA | 28 | 1.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_1_year | 0 | 0.0 | 0.0 | 0.0 | 0.0 |
| years_1_5 | 2 | 12.5 | 12.5 | 12.5 | 12.5 |
| years_6_10 | 4 | 25.0 | 25.0 | 37.5 | 37.5 |
| years_11_15 | 3 | 18.8 | 18.8 | 56.2 | 56.2 |
| years_16_20 | 2 | 12.5 | 12.5 | 68.8 | 68.8 |
| years_21_more | 5 | 31.2 | 31.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c2a1 <- as.factor(d[,"c2a1"])
levels(c2a1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2a1 <- ordered(c2a1, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2a1)
new.d <- apply_labels(new.d, c2a1 = "walk in the neighborhood-current")
temp.d <- data.frame (new.d, c2a1)
c2a2 <- as.factor(d[,"c2a2"])
levels(c2a1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2a2 <- ordered(c2a2, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2a2)
new.d <- apply_labels(new.d, c2a2 = "walk in the neighborhood-age 31 up")
temp.d <- data.frame (new.d, c2a2)
c2a3 <- as.factor(d[,"c2a3"])
levels(c2a1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2a3 <- ordered(c2a3, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2a3)
new.d <- apply_labels(new.d, c2a3 = "walk in the neighborhood-Childhood or young")
temp.d <- data.frame (new.d, c2a3)
result<-questionr::freq(temp.d$c2a1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1637 | 46.0 | 47.0 | 46.0 | 47.0 |
| Agree | 1174 | 33.0 | 33.7 | 79.0 | 80.8 |
| Neutral | 431 | 12.1 | 12.4 | 91.1 | 93.2 |
| Disagree | 176 | 4.9 | 5.1 | 96.1 | 98.2 |
| Strongly_Disagree | 56 | 1.6 | 1.6 | 97.7 | 99.8 |
| Scantron_Error | 6 | 0.2 | 0.2 | 97.8 | 100.0 |
| NA | 77 | 2.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c2a2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
result<-questionr::freq(temp.d$c2a3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 114 | 35.5 | 36.4 | 35.5 | 36.4 |
| Agree | 131 | 40.8 | 41.9 | 76.3 | 78.3 |
| Neutral | 45 | 14.0 | 14.4 | 90.3 | 92.7 |
| Disagree | 20 | 6.2 | 6.4 | 96.6 | 99.0 |
| Strongly_Disagree | 3 | 0.9 | 1.0 | 97.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.5 | 100.0 |
| NA | 8 | 2.5 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 109 | 51.9 | 52.7 | 51.9 | 52.7 |
| Agree | 60 | 28.6 | 29.0 | 80.5 | 81.6 |
| Neutral | 29 | 13.8 | 14.0 | 94.3 | 95.7 |
| Disagree | 9 | 4.3 | 4.3 | 98.6 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 98.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.6 | 100.0 |
| NA | 3 | 1.4 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 158 | 50.2 | 51.6 | 50.2 | 51.6 |
| Agree | 98 | 31.1 | 32.0 | 81.3 | 83.7 |
| Neutral | 28 | 8.9 | 9.2 | 90.2 | 92.8 |
| Disagree | 16 | 5.1 | 5.2 | 95.2 | 98.0 |
| Strongly_Disagree | 5 | 1.6 | 1.6 | 96.8 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 97.1 | 100.0 |
| NA | 9 | 2.9 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 130 | 36.5 | 37.2 | 36.5 | 37.2 |
| Agree | 117 | 32.9 | 33.5 | 69.4 | 70.8 |
| Neutral | 68 | 19.1 | 19.5 | 88.5 | 90.3 |
| Disagree | 21 | 5.9 | 6.0 | 94.4 | 96.3 |
| Strongly_Disagree | 13 | 3.7 | 3.7 | 98.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.0 | 100.0 |
| NA | 7 | 2.0 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 252 | 43.1 | 44.0 | 43.1 | 44.0 |
| Agree | 196 | 33.5 | 34.2 | 76.6 | 78.2 |
| Neutral | 77 | 13.2 | 13.4 | 89.7 | 91.6 |
| Disagree | 35 | 6.0 | 6.1 | 95.7 | 97.7 |
| Strongly_Disagree | 12 | 2.1 | 2.1 | 97.8 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 97.9 | 100.0 |
| NA | 12 | 2.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 869 | 49.5 | 50.6 | 49.5 | 50.6 |
| Agree | 563 | 32.1 | 32.8 | 81.6 | 83.4 |
| Neutral | 183 | 10.4 | 10.7 | 92.1 | 94.1 |
| Disagree | 75 | 4.3 | 4.4 | 96.4 | 98.5 |
| Strongly_Disagree | 22 | 1.3 | 1.3 | 97.6 | 99.8 |
| Scantron_Error | 4 | 0.2 | 0.2 | 97.8 | 100.0 |
| NA | 38 | 2.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 5 | 31.2 | 31.2 | 31.2 | 31.2 |
| Agree | 9 | 56.2 | 56.2 | 87.5 | 87.5 |
| Neutral | 1 | 6.2 | 6.2 | 93.8 | 93.8 |
| Disagree | 0 | 0.0 | 0.0 | 93.8 | 93.8 |
| Strongly_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
c2b1 <- as.factor(d[,"c2b1"])
levels(c2b1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2b1 <- ordered(c2b1, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2b1)
new.d <- apply_labels(new.d, c2b1 = "Violence in the neighborhood-current")
temp.d <- data.frame (new.d, c2b1)
c2b2 <- as.factor(d[,"c2b2"])
levels(c2b1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2b2 <- ordered(c2b2, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2b2)
new.d <- apply_labels(new.d, c2b2 = "Violence in the neighborhood-age 31 up")
temp.d <- data.frame (new.d, c2b2)
c2b3 <- as.factor(d[,"c2b3"])
levels(c2b1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2b3 <- ordered(c2b3, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2b3)
new.d <- apply_labels(new.d, c2b3 = "Violence in the neighborhood-Childhood or young")
temp.d <- data.frame (new.d, c2b3)
result<-questionr::freq(temp.d$c2b1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1399 | 39.3 | 40.6 | 39.3 | 40.6 |
| Agree | 1094 | 30.8 | 31.7 | 70.1 | 72.3 |
| Neutral | 523 | 14.7 | 15.2 | 84.8 | 87.5 |
| Disagree | 299 | 8.4 | 8.7 | 93.2 | 96.1 |
| Strongly_Disagree | 129 | 3.6 | 3.7 | 96.8 | 99.9 |
| Scantron_Error | 4 | 0.1 | 0.1 | 96.9 | 100.0 |
| NA | 109 | 3.1 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c2b2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
result<-questionr::freq(temp.d$c2b3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 89 | 27.7 | 28.6 | 27.7 | 28.6 |
| Agree | 106 | 33.0 | 34.1 | 60.7 | 62.7 |
| Neutral | 63 | 19.6 | 20.3 | 80.4 | 83.0 |
| Disagree | 42 | 13.1 | 13.5 | 93.5 | 96.5 |
| Strongly_Disagree | 11 | 3.4 | 3.5 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 10 | 3.1 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 92 | 43.8 | 44.4 | 43.8 | 44.4 |
| Agree | 55 | 26.2 | 26.6 | 70.0 | 71.0 |
| Neutral | 38 | 18.1 | 18.4 | 88.1 | 89.4 |
| Disagree | 14 | 6.7 | 6.8 | 94.8 | 96.1 |
| Strongly_Disagree | 8 | 3.8 | 3.9 | 98.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.6 | 100.0 |
| NA | 3 | 1.4 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 140 | 44.4 | 46.1 | 44.4 | 46.1 |
| Agree | 92 | 29.2 | 30.3 | 73.7 | 76.3 |
| Neutral | 39 | 12.4 | 12.8 | 86.0 | 89.1 |
| Disagree | 23 | 7.3 | 7.6 | 93.3 | 96.7 |
| Strongly_Disagree | 10 | 3.2 | 3.3 | 96.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.5 | 100.0 |
| NA | 11 | 3.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 96 | 27.0 | 28.0 | 27.0 | 28.0 |
| Agree | 93 | 26.1 | 27.1 | 53.1 | 55.1 |
| Neutral | 96 | 27.0 | 28.0 | 80.1 | 83.1 |
| Disagree | 39 | 11.0 | 11.4 | 91.0 | 94.5 |
| Strongly_Disagree | 19 | 5.3 | 5.5 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 13 | 3.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 194 | 33.2 | 34.5 | 33.2 | 34.5 |
| Agree | 192 | 32.8 | 34.1 | 66.0 | 68.6 |
| Neutral | 76 | 13.0 | 13.5 | 79.0 | 82.1 |
| Disagree | 69 | 11.8 | 12.3 | 90.8 | 94.3 |
| Strongly_Disagree | 30 | 5.1 | 5.3 | 95.9 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 96.2 | 100.0 |
| NA | 22 | 3.8 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 783 | 44.6 | 46.0 | 44.6 | 46.0 |
| Agree | 551 | 31.4 | 32.3 | 76.1 | 78.3 |
| Neutral | 209 | 11.9 | 12.3 | 88.0 | 90.6 |
| Disagree | 109 | 6.2 | 6.4 | 94.2 | 96.9 |
| Strongly_Disagree | 50 | 2.9 | 2.9 | 97.0 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 97.1 | 100.0 |
| NA | 50 | 2.9 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 5 | 31.2 | 31.2 | 31.2 | 31.2 |
| Agree | 5 | 31.2 | 31.2 | 62.5 | 62.5 |
| Neutral | 2 | 12.5 | 12.5 | 75.0 | 75.0 |
| Disagree | 3 | 18.8 | 18.8 | 93.8 | 93.8 |
| Strongly_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
c2c1 <- as.factor(d[,"c2c1"])
levels(c2c1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2c1 <- ordered(c2c1, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2c1)
new.d <- apply_labels(new.d, c2c1 = "safe from crime in the neighborhood-current")
temp.d <- data.frame (new.d, c2c1)
c2c2 <- as.factor(d[,"c2c2"])
levels(c2c1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2c2 <- ordered(c2c2, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2c2)
new.d <- apply_labels(new.d, c2c2 = "safe from crime in the neighborhood-age 31 up")
temp.d <- data.frame (new.d, c2c2)
c2c3 <- as.factor(d[,"c2c3"])
levels(c2c1) <- list(Strongly_Agree="1",
Agree="2",
Neutral="3",
Disagree="4",
Strongly_Disagree="5",
Scantron_Error="*")
c2c3 <- ordered(c2c3, c("Strongly_Agree", "Agree", "Neutral", "Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, c2c3)
new.d <- apply_labels(new.d, c2c3 = "safe from crime in the neighborhood-Childhood or young")
temp.d <- data.frame (new.d, c2c3)
result<-questionr::freq(temp.d$c2c1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1026 | 28.8 | 29.9 | 28.8 | 29.9 |
| Agree | 1073 | 30.2 | 31.2 | 59.0 | 61.1 |
| Neutral | 772 | 21.7 | 22.5 | 80.7 | 83.6 |
| Disagree | 436 | 12.3 | 12.7 | 93.0 | 96.3 |
| Strongly_Disagree | 123 | 3.5 | 3.6 | 96.4 | 99.9 |
| Scantron_Error | 5 | 0.1 | 0.1 | 96.6 | 100.0 |
| NA | 122 | 3.4 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c2c2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
result<-questionr::freq(temp.d$c2c3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 3557 | 100 | NA | 100 | NA |
| Total | 3557 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 68 | 21.2 | 21.9 | 21.2 | 21.9 |
| Agree | 89 | 27.7 | 28.6 | 48.9 | 50.5 |
| Neutral | 81 | 25.2 | 26.0 | 74.1 | 76.5 |
| Disagree | 62 | 19.3 | 19.9 | 93.5 | 96.5 |
| Strongly_Disagree | 11 | 3.4 | 3.5 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 10 | 3.1 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 63 | 30.0 | 30.9 | 30.0 | 30.9 |
| Agree | 59 | 28.1 | 28.9 | 58.1 | 59.8 |
| Neutral | 46 | 21.9 | 22.5 | 80.0 | 82.4 |
| Disagree | 28 | 13.3 | 13.7 | 93.3 | 96.1 |
| Strongly_Disagree | 8 | 3.8 | 3.9 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 6 | 2.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 84 | 26.7 | 27.8 | 26.7 | 27.8 |
| Agree | 102 | 32.4 | 33.8 | 59.0 | 61.6 |
| Neutral | 76 | 24.1 | 25.2 | 83.2 | 86.8 |
| Disagree | 32 | 10.2 | 10.6 | 93.3 | 97.4 |
| Strongly_Disagree | 8 | 2.5 | 2.6 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 69 | 19.4 | 20.0 | 19.4 | 20.0 |
| Agree | 78 | 21.9 | 22.6 | 41.3 | 42.6 |
| Neutral | 112 | 31.5 | 32.5 | 72.8 | 75.1 |
| Disagree | 63 | 17.7 | 18.3 | 90.4 | 93.3 |
| Strongly_Disagree | 23 | 6.5 | 6.7 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 11 | 3.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 156 | 26.7 | 27.6 | 26.7 | 27.6 |
| Agree | 180 | 30.8 | 31.9 | 57.4 | 59.5 |
| Neutral | 122 | 20.9 | 21.6 | 78.3 | 81.1 |
| Disagree | 77 | 13.2 | 13.6 | 91.5 | 94.7 |
| Strongly_Disagree | 28 | 4.8 | 5.0 | 96.2 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 96.6 | 100.0 |
| NA | 20 | 3.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 580 | 33.1 | 34.3 | 33.1 | 34.3 |
| Agree | 561 | 32.0 | 33.2 | 65.1 | 67.4 |
| Neutral | 330 | 18.8 | 19.5 | 83.9 | 86.9 |
| Disagree | 173 | 9.9 | 10.2 | 93.7 | 97.2 |
| Strongly_Disagree | 45 | 2.6 | 2.7 | 96.3 | 99.8 |
| Scantron_Error | 3 | 0.2 | 0.2 | 96.5 | 100.0 |
| NA | 62 | 3.5 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 1754 | 100 | NA | 100 | NA |
| Total | 1754 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 6 | 37.5 | 37.5 | 37.5 | 37.5 |
| Agree | 4 | 25.0 | 25.0 | 62.5 | 62.5 |
| Neutral | 5 | 31.2 | 31.2 | 93.8 | 93.8 |
| Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 0 | 0 | NaN | 0 | NaN |
| Agree | 0 | 0 | NaN | 0 | NaN |
| Neutral | 0 | 0 | NaN | 0 | NaN |
| Disagree | 0 | 0 | NaN | 0 | NaN |
| Strongly_Disagree | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 16 | 100 | NA | 100 | NA |
| Total | 16 | 100 | 100 | 100 | 100 |
c3a1 <- as.factor(d[,"c3a1"])
levels(c3a1) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3a1 <- ordered(c3a1, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3a1)
new.d <- apply_labels(new.d, c3a1 = "A lot of noise-Current")
temp.d <- data.frame (new.d, c3a1)
c3a2 <- as.factor(d[,"c3a2"])
levels(c3a2) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3a2 <- ordered(c3a2, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3a2)
new.d <- apply_labels(new.d, c3a2 = "A lot of noise-age 31 up")
temp.d <- data.frame (new.d, c3a2)
c3a3 <- as.factor(d[,"c3a3"])
levels(c3a3) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3a3 <- ordered(c3a3, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3a3)
new.d <- apply_labels(new.d, c3a3 = "A lot of noise-Childhood or young")
temp.d <- data.frame (new.d, c3a3)
result<-questionr::freq(temp.d$c3a1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2430 | 68.3 | 70.3 | 68.3 | 70.3 |
| Somewhat_serious | 642 | 18.0 | 18.6 | 86.4 | 88.8 |
| Very_serious | 245 | 6.9 | 7.1 | 93.3 | 95.9 |
| Dont_know | 139 | 3.9 | 4.0 | 97.2 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 97.2 | 100.0 |
| NA | 98 | 2.8 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3a2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2310 | 64.9 | 69.3 | 64.9 | 69.3 |
| Somewhat_serious | 705 | 19.8 | 21.1 | 84.8 | 90.4 |
| Very_serious | 141 | 4.0 | 4.2 | 88.7 | 94.6 |
| Dont_know | 176 | 4.9 | 5.3 | 93.7 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 93.8 | 100.0 |
| NA | 222 | 6.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3a3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2551 | 71.7 | 77.2 | 71.7 | 77.2 |
| Somewhat_serious | 397 | 11.2 | 12.0 | 82.9 | 89.2 |
| Very_serious | 90 | 2.5 | 2.7 | 85.4 | 91.9 |
| Dont_know | 264 | 7.4 | 8.0 | 92.8 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 92.9 | 100.0 |
| NA | 252 | 7.1 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 161 | 50.2 | 51.1 | 50.2 | 51.1 |
| Somewhat_serious | 96 | 29.9 | 30.5 | 80.1 | 81.6 |
| Very_serious | 53 | 16.5 | 16.8 | 96.6 | 98.4 |
| Dont_know | 5 | 1.6 | 1.6 | 98.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.1 | 100.0 |
| NA | 6 | 1.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 163 | 50.8 | 52.2 | 50.8 | 52.2 |
| Somewhat_serious | 116 | 36.1 | 37.2 | 86.9 | 89.4 |
| Very_serious | 24 | 7.5 | 7.7 | 94.4 | 97.1 |
| Dont_know | 9 | 2.8 | 2.9 | 97.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.2 | 100.0 |
| NA | 9 | 2.8 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 235 | 73.2 | 75.8 | 73.2 | 75.8 |
| Somewhat_serious | 44 | 13.7 | 14.2 | 86.9 | 90.0 |
| Very_serious | 14 | 4.4 | 4.5 | 91.3 | 94.5 |
| Dont_know | 17 | 5.3 | 5.5 | 96.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.6 | 100.0 |
| NA | 11 | 3.4 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 124 | 59.0 | 60.5 | 59.0 | 60.5 |
| Somewhat_serious | 59 | 28.1 | 28.8 | 87.1 | 89.3 |
| Very_serious | 19 | 9.0 | 9.3 | 96.2 | 98.5 |
| Dont_know | 3 | 1.4 | 1.5 | 97.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.6 | 100.0 |
| NA | 5 | 2.4 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 128 | 61.0 | 63.4 | 61.0 | 63.4 |
| Somewhat_serious | 54 | 25.7 | 26.7 | 86.7 | 90.1 |
| Very_serious | 13 | 6.2 | 6.4 | 92.9 | 96.5 |
| Dont_know | 7 | 3.3 | 3.5 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 8 | 3.8 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 149 | 71.0 | 74.9 | 71.0 | 74.9 |
| Somewhat_serious | 30 | 14.3 | 15.1 | 85.2 | 89.9 |
| Very_serious | 6 | 2.9 | 3.0 | 88.1 | 93.0 |
| Dont_know | 14 | 6.7 | 7.0 | 94.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.8 | 100.0 |
| NA | 11 | 5.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 217 | 68.9 | 71.1 | 68.9 | 71.1 |
| Somewhat_serious | 60 | 19.0 | 19.7 | 87.9 | 90.8 |
| Very_serious | 21 | 6.7 | 6.9 | 94.6 | 97.7 |
| Dont_know | 7 | 2.2 | 2.3 | 96.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.8 | 100.0 |
| NA | 10 | 3.2 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 195 | 61.9 | 65.4 | 61.9 | 65.4 |
| Somewhat_serious | 66 | 21.0 | 22.1 | 82.9 | 87.6 |
| Very_serious | 22 | 7.0 | 7.4 | 89.8 | 95.0 |
| Dont_know | 15 | 4.8 | 5.0 | 94.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.6 | 100.0 |
| NA | 17 | 5.4 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 208 | 66.0 | 70.0 | 66.0 | 70.0 |
| Somewhat_serious | 53 | 16.8 | 17.8 | 82.9 | 87.9 |
| Very_serious | 15 | 4.8 | 5.1 | 87.6 | 92.9 |
| Dont_know | 21 | 6.7 | 7.1 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 18 | 5.7 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 238 | 66.9 | 69.6 | 66.9 | 69.6 |
| Somewhat_serious | 67 | 18.8 | 19.6 | 85.7 | 89.2 |
| Very_serious | 19 | 5.3 | 5.6 | 91.0 | 94.7 |
| Dont_know | 18 | 5.1 | 5.3 | 96.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.1 | 100.0 |
| NA | 14 | 3.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 219 | 61.5 | 67.6 | 61.5 | 67.6 |
| Somewhat_serious | 82 | 23.0 | 25.3 | 84.6 | 92.9 |
| Very_serious | 8 | 2.2 | 2.5 | 86.8 | 95.4 |
| Dont_know | 15 | 4.2 | 4.6 | 91.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.0 | 100.0 |
| NA | 32 | 9.0 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 238 | 66.9 | 74.1 | 66.9 | 74.1 |
| Somewhat_serious | 48 | 13.5 | 15.0 | 80.3 | 89.1 |
| Very_serious | 7 | 2.0 | 2.2 | 82.3 | 91.3 |
| Dont_know | 28 | 7.9 | 8.7 | 90.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.2 | 100.0 |
| NA | 35 | 9.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 434 | 74.2 | 76.1 | 74.2 | 76.1 |
| Somewhat_serious | 75 | 12.8 | 13.2 | 87.0 | 89.3 |
| Very_serious | 26 | 4.4 | 4.6 | 91.5 | 93.9 |
| Dont_know | 34 | 5.8 | 6.0 | 97.3 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 97.4 | 100.0 |
| NA | 15 | 2.6 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 400 | 68.4 | 74.3 | 68.4 | 74.3 |
| Somewhat_serious | 91 | 15.6 | 16.9 | 83.9 | 91.3 |
| Very_serious | 15 | 2.6 | 2.8 | 86.5 | 94.1 |
| Dont_know | 31 | 5.3 | 5.8 | 91.8 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 92.0 | 100.0 |
| NA | 47 | 8.0 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 422 | 72.1 | 78.7 | 72.1 | 78.7 |
| Somewhat_serious | 54 | 9.2 | 10.1 | 81.4 | 88.8 |
| Very_serious | 14 | 2.4 | 2.6 | 83.8 | 91.4 |
| Dont_know | 45 | 7.7 | 8.4 | 91.5 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 91.6 | 100.0 |
| NA | 49 | 8.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1245 | 71.0 | 73.0 | 71.0 | 73.0 |
| Somewhat_serious | 281 | 16.0 | 16.5 | 87.0 | 89.4 |
| Very_serious | 107 | 6.1 | 6.3 | 93.1 | 95.7 |
| Dont_know | 71 | 4.0 | 4.2 | 97.1 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 97.3 | 100.0 |
| NA | 48 | 2.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1194 | 68.1 | 72.5 | 68.1 | 72.5 |
| Somewhat_serious | 294 | 16.8 | 17.9 | 84.8 | 90.4 |
| Very_serious | 59 | 3.4 | 3.6 | 88.2 | 94.0 |
| Dont_know | 97 | 5.5 | 5.9 | 93.7 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 93.8 | 100.0 |
| NA | 108 | 6.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1287 | 73.4 | 79.1 | 73.4 | 79.1 |
| Somewhat_serious | 167 | 9.5 | 10.3 | 82.9 | 89.4 |
| Very_serious | 34 | 1.9 | 2.1 | 84.8 | 91.5 |
| Dont_know | 137 | 7.8 | 8.4 | 92.6 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.8 | 100.0 |
| NA | 127 | 7.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 11 | 68.8 | 68.8 | 68.8 | 68.8 |
| Somewhat_serious | 4 | 25.0 | 25.0 | 93.8 | 93.8 |
| Very_serious | 0 | 0.0 | 0.0 | 93.8 | 93.8 |
| Dont_know | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 11 | 68.8 | 73.3 | 68.8 | 73.3 |
| Somewhat_serious | 2 | 12.5 | 13.3 | 81.2 | 86.7 |
| Very_serious | 0 | 0.0 | 0.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 12 | 75.0 | 80.0 | 75.0 | 80.0 |
| Somewhat_serious | 1 | 6.2 | 6.7 | 81.2 | 86.7 |
| Very_serious | 0 | 0.0 | 0.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c3b1 <- as.factor(d[,"c3b1"])
levels(c3b1) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3b1 <- ordered(c3b1, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3b1)
new.d <- apply_labels(new.d, c3b1 = "A lot of noise-Current")
temp.d <- data.frame (new.d, c3b1)
c3b2 <- as.factor(d[,"c3b2"])
levels(c3b2) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3b2 <- ordered(c3b2, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3b2)
new.d <- apply_labels(new.d, c3b2 = "A lot of noise-age 31 up")
temp.d <- data.frame (new.d, c3b2)
c3b3 <- as.factor(d[,"c3b3"])
levels(c3b3) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3b3 <- ordered(c3b3, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3b3)
new.d <- apply_labels(new.d, c3b3 = "A lot of noise-Childhood or young")
temp.d <- data.frame (new.d, c3b3)
result<-questionr::freq(temp.d$c3b1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2816 | 79.2 | 82.1 | 79.2 | 82.1 |
| Somewhat_serious | 435 | 12.2 | 12.7 | 91.4 | 94.8 |
| Very_serious | 99 | 2.8 | 2.9 | 94.2 | 97.6 |
| Dont_know | 79 | 2.2 | 2.3 | 96.4 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 96.5 | 100.0 |
| NA | 126 | 3.5 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3b2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2541 | 71.4 | 77.0 | 71.4 | 77.0 |
| Somewhat_serious | 538 | 15.1 | 16.3 | 86.6 | 93.3 |
| Very_serious | 94 | 2.6 | 2.8 | 89.2 | 96.2 |
| Dont_know | 124 | 3.5 | 3.8 | 92.7 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 92.8 | 100.0 |
| NA | 257 | 7.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3b3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2531 | 71.2 | 77.1 | 71.2 | 77.1 |
| Somewhat_serious | 437 | 12.3 | 13.3 | 83.4 | 90.4 |
| Very_serious | 107 | 3.0 | 3.3 | 86.4 | 93.6 |
| Dont_know | 207 | 5.8 | 6.3 | 92.3 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.3 | 100.0 |
| NA | 273 | 7.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 229 | 71.3 | 73.4 | 71.3 | 73.4 |
| Somewhat_serious | 61 | 19.0 | 19.6 | 90.3 | 92.9 |
| Very_serious | 17 | 5.3 | 5.4 | 95.6 | 98.4 |
| Dont_know | 5 | 1.6 | 1.6 | 97.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.2 | 100.0 |
| NA | 9 | 2.8 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 213 | 66.4 | 68.7 | 66.4 | 68.7 |
| Somewhat_serious | 73 | 22.7 | 23.5 | 89.1 | 92.3 |
| Very_serious | 14 | 4.4 | 4.5 | 93.5 | 96.8 |
| Dont_know | 10 | 3.1 | 3.2 | 96.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.6 | 100.0 |
| NA | 11 | 3.4 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 235 | 73.2 | 76.1 | 73.2 | 76.1 |
| Somewhat_serious | 45 | 14.0 | 14.6 | 87.2 | 90.6 |
| Very_serious | 12 | 3.7 | 3.9 | 91.0 | 94.5 |
| Dont_know | 17 | 5.3 | 5.5 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 12 | 3.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 158 | 75.2 | 77.5 | 75.2 | 77.5 |
| Somewhat_serious | 37 | 17.6 | 18.1 | 92.9 | 95.6 |
| Very_serious | 8 | 3.8 | 3.9 | 96.7 | 99.5 |
| Dont_know | 1 | 0.5 | 0.5 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 6 | 2.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 145 | 69.0 | 72.1 | 69.0 | 72.1 |
| Somewhat_serious | 39 | 18.6 | 19.4 | 87.6 | 91.5 |
| Very_serious | 11 | 5.2 | 5.5 | 92.9 | 97.0 |
| Dont_know | 6 | 2.9 | 3.0 | 95.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.7 | 100.0 |
| NA | 9 | 4.3 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 153 | 72.9 | 77.3 | 72.9 | 77.3 |
| Somewhat_serious | 27 | 12.9 | 13.6 | 85.7 | 90.9 |
| Very_serious | 7 | 3.3 | 3.5 | 89.0 | 94.4 |
| Dont_know | 11 | 5.2 | 5.6 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 12 | 5.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 258 | 81.9 | 84.6 | 81.9 | 84.6 |
| Somewhat_serious | 33 | 10.5 | 10.8 | 92.4 | 95.4 |
| Very_serious | 9 | 2.9 | 3.0 | 95.2 | 98.4 |
| Dont_know | 5 | 1.6 | 1.6 | 96.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.8 | 100.0 |
| NA | 10 | 3.2 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 229 | 72.7 | 77.1 | 72.7 | 77.1 |
| Somewhat_serious | 47 | 14.9 | 15.8 | 87.6 | 92.9 |
| Very_serious | 8 | 2.5 | 2.7 | 90.2 | 95.6 |
| Dont_know | 13 | 4.1 | 4.4 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 18 | 5.7 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 209 | 66.3 | 70.4 | 66.3 | 70.4 |
| Somewhat_serious | 54 | 17.1 | 18.2 | 83.5 | 88.6 |
| Very_serious | 13 | 4.1 | 4.4 | 87.6 | 92.9 |
| Dont_know | 21 | 6.7 | 7.1 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 18 | 5.7 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 261 | 73.3 | 77.0 | 73.3 | 77.0 |
| Somewhat_serious | 55 | 15.4 | 16.2 | 88.8 | 93.2 |
| Very_serious | 14 | 3.9 | 4.1 | 92.7 | 97.3 |
| Dont_know | 9 | 2.5 | 2.7 | 95.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.2 | 100.0 |
| NA | 17 | 4.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 233 | 65.4 | 71.5 | 65.4 | 71.5 |
| Somewhat_serious | 63 | 17.7 | 19.3 | 83.1 | 90.8 |
| Very_serious | 15 | 4.2 | 4.6 | 87.4 | 95.4 |
| Dont_know | 15 | 4.2 | 4.6 | 91.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.6 | 100.0 |
| NA | 30 | 8.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 230 | 64.6 | 71.2 | 64.6 | 71.2 |
| Somewhat_serious | 59 | 16.6 | 18.3 | 81.2 | 89.5 |
| Very_serious | 9 | 2.5 | 2.8 | 83.7 | 92.3 |
| Dont_know | 25 | 7.0 | 7.7 | 90.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.7 | 100.0 |
| NA | 33 | 9.3 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 456 | 77.9 | 80.4 | 77.9 | 80.4 |
| Somewhat_serious | 69 | 11.8 | 12.2 | 89.7 | 92.6 |
| Very_serious | 21 | 3.6 | 3.7 | 93.3 | 96.3 |
| Dont_know | 20 | 3.4 | 3.5 | 96.8 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 96.9 | 100.0 |
| NA | 18 | 3.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 398 | 68.0 | 75.5 | 68.0 | 75.5 |
| Somewhat_serious | 89 | 15.2 | 16.9 | 83.2 | 92.4 |
| Very_serious | 13 | 2.2 | 2.5 | 85.5 | 94.9 |
| Dont_know | 25 | 4.3 | 4.7 | 89.7 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 90.1 | 100.0 |
| NA | 58 | 9.9 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 407 | 69.6 | 76.9 | 69.6 | 76.9 |
| Somewhat_serious | 64 | 10.9 | 12.1 | 80.5 | 89.0 |
| Very_serious | 19 | 3.2 | 3.6 | 83.8 | 92.6 |
| Dont_know | 38 | 6.5 | 7.2 | 90.3 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 90.4 | 100.0 |
| NA | 56 | 9.6 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1443 | 82.3 | 85.5 | 82.3 | 85.5 |
| Somewhat_serious | 176 | 10.0 | 10.4 | 92.3 | 95.9 |
| Very_serious | 29 | 1.7 | 1.7 | 94.0 | 97.6 |
| Dont_know | 39 | 2.2 | 2.3 | 96.2 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 96.2 | 100.0 |
| NA | 66 | 3.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1311 | 74.7 | 80.7 | 74.7 | 80.7 |
| Somewhat_serious | 225 | 12.8 | 13.9 | 87.6 | 94.6 |
| Very_serious | 32 | 1.8 | 2.0 | 89.4 | 96.6 |
| Dont_know | 55 | 3.1 | 3.4 | 92.5 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.6 | 100.0 |
| NA | 130 | 7.4 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1285 | 73.3 | 79.7 | 73.3 | 79.7 |
| Somewhat_serious | 185 | 10.5 | 11.5 | 83.8 | 91.1 |
| Very_serious | 47 | 2.7 | 2.9 | 86.5 | 94.0 |
| Dont_know | 95 | 5.4 | 5.9 | 91.9 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.0 | 100.0 |
| NA | 141 | 8.0 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 11 | 68.8 | 68.8 | 68.8 | 68.8 |
| Somewhat_serious | 4 | 25.0 | 25.0 | 93.8 | 93.8 |
| Very_serious | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 12 | 75.0 | 80.0 | 75.0 | 80.0 |
| Somewhat_serious | 2 | 12.5 | 13.3 | 87.5 | 93.3 |
| Very_serious | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 12 | 75.0 | 80 | 75.0 | 80 |
| Somewhat_serious | 3 | 18.8 | 20 | 93.8 | 100 |
| Very_serious | 0 | 0.0 | 0 | 93.8 | 100 |
| Dont_know | 0 | 0.0 | 0 | 93.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 93.8 | 100 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
c3c1 <- as.factor(d[,"c3c1"])
levels(c3c1) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3c1 <- ordered(c3c1, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3c1)
new.d <- apply_labels(new.d, c3c1 = "Trash and litter-Current")
temp.d <- data.frame (new.d, c3c1)
c3c2 <- as.factor(d[,"c3c2"])
levels(c3c2) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3c2 <- ordered(c3c2, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3c2)
new.d <- apply_labels(new.d, c3c2 = "Trash and litter-age 31 up")
temp.d <- data.frame (new.d, c3c2)
c3c3 <- as.factor(d[,"c3c3"])
levels(c3c3) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3c3 <- ordered(c3c3, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3c3)
new.d <- apply_labels(new.d, c3c3 = "Trash and litter-Childhood or young")
temp.d <- data.frame (new.d, c3c3)
result<-questionr::freq(temp.d$c3c1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2832 | 79.6 | 82.6 | 79.6 | 82.6 |
| Somewhat_serious | 371 | 10.4 | 10.8 | 90.0 | 93.4 |
| Very_serious | 152 | 4.3 | 4.4 | 94.3 | 97.8 |
| Dont_know | 73 | 2.1 | 2.1 | 96.4 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 96.4 | 100.0 |
| NA | 127 | 3.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3c2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2637 | 74.1 | 79.9 | 74.1 | 79.9 |
| Somewhat_serious | 453 | 12.7 | 13.7 | 86.9 | 93.6 |
| Very_serious | 103 | 2.9 | 3.1 | 89.8 | 96.7 |
| Dont_know | 107 | 3.0 | 3.2 | 92.8 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.8 | 100.0 |
| NA | 255 | 7.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3c3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2561 | 72.0 | 77.9 | 72.0 | 77.9 |
| Somewhat_serious | 430 | 12.1 | 13.1 | 84.1 | 91.0 |
| Very_serious | 121 | 3.4 | 3.7 | 87.5 | 94.7 |
| Dont_know | 172 | 4.8 | 5.2 | 92.3 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.4 | 100.0 |
| NA | 271 | 7.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 235 | 73.2 | 75.3 | 73.2 | 75.3 |
| Somewhat_serious | 53 | 16.5 | 17.0 | 89.7 | 92.3 |
| Very_serious | 21 | 6.5 | 6.7 | 96.3 | 99.0 |
| Dont_know | 3 | 0.9 | 1.0 | 97.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.2 | 100.0 |
| NA | 9 | 2.8 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 234 | 72.9 | 76.2 | 72.9 | 76.2 |
| Somewhat_serious | 57 | 17.8 | 18.6 | 90.7 | 94.8 |
| Very_serious | 11 | 3.4 | 3.6 | 94.1 | 98.4 |
| Dont_know | 5 | 1.6 | 1.6 | 95.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.6 | 100.0 |
| NA | 14 | 4.4 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 253 | 78.8 | 81.9 | 78.8 | 81.9 |
| Somewhat_serious | 38 | 11.8 | 12.3 | 90.7 | 94.2 |
| Very_serious | 9 | 2.8 | 2.9 | 93.5 | 97.1 |
| Dont_know | 9 | 2.8 | 2.9 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 12 | 3.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 157 | 74.8 | 77.0 | 74.8 | 77.0 |
| Somewhat_serious | 27 | 12.9 | 13.2 | 87.6 | 90.2 |
| Very_serious | 17 | 8.1 | 8.3 | 95.7 | 98.5 |
| Dont_know | 3 | 1.4 | 1.5 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 6 | 2.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 156 | 74.3 | 77.6 | 74.3 | 77.6 |
| Somewhat_serious | 29 | 13.8 | 14.4 | 88.1 | 92.0 |
| Very_serious | 10 | 4.8 | 5.0 | 92.9 | 97.0 |
| Dont_know | 6 | 2.9 | 3.0 | 95.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.7 | 100.0 |
| NA | 9 | 4.3 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 148 | 70.5 | 75.1 | 70.5 | 75.1 |
| Somewhat_serious | 30 | 14.3 | 15.2 | 84.8 | 90.4 |
| Very_serious | 9 | 4.3 | 4.6 | 89.0 | 94.9 |
| Dont_know | 10 | 4.8 | 5.1 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 13 | 6.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 260 | 82.5 | 85.8 | 82.5 | 85.8 |
| Somewhat_serious | 25 | 7.9 | 8.3 | 90.5 | 94.1 |
| Very_serious | 15 | 4.8 | 5.0 | 95.2 | 99.0 |
| Dont_know | 3 | 1.0 | 1.0 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 234 | 74.3 | 79.1 | 74.3 | 79.1 |
| Somewhat_serious | 40 | 12.7 | 13.5 | 87.0 | 92.6 |
| Very_serious | 12 | 3.8 | 4.1 | 90.8 | 96.6 |
| Dont_know | 10 | 3.2 | 3.4 | 94.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.0 | 100.0 |
| NA | 19 | 6.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 210 | 66.7 | 70.9 | 66.7 | 70.9 |
| Somewhat_serious | 46 | 14.6 | 15.5 | 81.3 | 86.5 |
| Very_serious | 22 | 7.0 | 7.4 | 88.3 | 93.9 |
| Dont_know | 18 | 5.7 | 6.1 | 94.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.0 | 100.0 |
| NA | 19 | 6.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 260 | 73.0 | 75.8 | 73.0 | 75.8 |
| Somewhat_serious | 49 | 13.8 | 14.3 | 86.8 | 90.1 |
| Very_serious | 23 | 6.5 | 6.7 | 93.3 | 96.8 |
| Dont_know | 11 | 3.1 | 3.2 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 13 | 3.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 226 | 63.5 | 68.9 | 63.5 | 68.9 |
| Somewhat_serious | 69 | 19.4 | 21.0 | 82.9 | 89.9 |
| Very_serious | 23 | 6.5 | 7.0 | 89.3 | 97.0 |
| Dont_know | 10 | 2.8 | 3.0 | 92.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.1 | 100.0 |
| NA | 28 | 7.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 226 | 63.5 | 69.3 | 63.5 | 69.3 |
| Somewhat_serious | 68 | 19.1 | 20.9 | 82.6 | 90.2 |
| Very_serious | 14 | 3.9 | 4.3 | 86.5 | 94.5 |
| Dont_know | 18 | 5.1 | 5.5 | 91.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.6 | 100.0 |
| NA | 30 | 8.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 447 | 76.4 | 79.7 | 76.4 | 79.7 |
| Somewhat_serious | 66 | 11.3 | 11.8 | 87.7 | 91.4 |
| Very_serious | 28 | 4.8 | 5.0 | 92.5 | 96.4 |
| Dont_know | 19 | 3.2 | 3.4 | 95.7 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 95.9 | 100.0 |
| NA | 24 | 4.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 407 | 69.6 | 76.6 | 69.6 | 76.6 |
| Somewhat_serious | 85 | 14.5 | 16.0 | 84.1 | 92.7 |
| Very_serious | 15 | 2.6 | 2.8 | 86.7 | 95.5 |
| Dont_know | 23 | 3.9 | 4.3 | 90.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 90.8 | 100.0 |
| NA | 54 | 9.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 404 | 69.1 | 76.7 | 69.1 | 76.7 |
| Somewhat_serious | 72 | 12.3 | 13.7 | 81.4 | 90.3 |
| Very_serious | 18 | 3.1 | 3.4 | 84.4 | 93.7 |
| Dont_know | 32 | 5.5 | 6.1 | 89.9 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 90.1 | 100.0 |
| NA | 58 | 9.9 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1460 | 83.2 | 86.3 | 83.2 | 86.3 |
| Somewhat_serious | 149 | 8.5 | 8.8 | 91.7 | 95.2 |
| Very_serious | 48 | 2.7 | 2.8 | 94.5 | 98.0 |
| Dont_know | 33 | 1.9 | 2.0 | 96.4 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 96.4 | 100.0 |
| NA | 63 | 3.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1368 | 78.0 | 84.2 | 78.0 | 84.2 |
| Somewhat_serious | 171 | 9.7 | 10.5 | 87.7 | 94.8 |
| Very_serious | 32 | 1.8 | 2.0 | 89.6 | 96.7 |
| Dont_know | 52 | 3.0 | 3.2 | 92.5 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.6 | 100.0 |
| NA | 130 | 7.4 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1308 | 74.6 | 80.9 | 74.6 | 80.9 |
| Somewhat_serious | 174 | 9.9 | 10.8 | 84.5 | 91.7 |
| Very_serious | 49 | 2.8 | 3.0 | 87.3 | 94.7 |
| Dont_know | 84 | 4.8 | 5.2 | 92.1 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.1 | 100.0 |
| NA | 138 | 7.9 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 13 | 81.2 | 81.2 | 81.2 | 81.2 |
| Somewhat_serious | 2 | 12.5 | 12.5 | 93.8 | 93.8 |
| Very_serious | 0 | 0.0 | 0.0 | 93.8 | 93.8 |
| Dont_know | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 12 | 75.0 | 80.0 | 75.0 | 80.0 |
| Somewhat_serious | 2 | 12.5 | 13.3 | 87.5 | 93.3 |
| Very_serious | 0 | 0.0 | 0.0 | 87.5 | 93.3 |
| Dont_know | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 12 | 75.0 | 80.0 | 75.0 | 80.0 |
| Somewhat_serious | 2 | 12.5 | 13.3 | 87.5 | 93.3 |
| Very_serious | 0 | 0.0 | 0.0 | 87.5 | 93.3 |
| Dont_know | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c3d1 <- as.factor(d[,"c3d1"])
levels(c3d1) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3d1 <- ordered(c3d1, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3d1)
new.d <- apply_labels(new.d, c3d1 = "Too much light at night-Current")
temp.d <- data.frame (new.d, c3d1)
c3d2 <- as.factor(d[,"c3d2"])
levels(c3d2) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3d2 <- ordered(c3d2, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3d2)
new.d <- apply_labels(new.d, c3d2 = "Too much light at night-age 31 up")
temp.d <- data.frame (new.d, c3d2)
c3d3 <- as.factor(d[,"c3d3"])
levels(c3d3) <- list(Non_Minor="1",
Somewhat_serious="2",
Very_serious="3",
Dont_know="88",
Scantron_Error="*")
c3d3 <- ordered(c3d3, c("Non_Minor", "Somewhat_serious", "Very_serious", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c3d3)
new.d <- apply_labels(new.d, c3d3 = "Too much light at night-Childhood or young")
temp.d <- data.frame (new.d, c3d3)
result<-questionr::freq(temp.d$c3d1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 3139 | 88.2 | 91.8 | 88.2 | 91.8 |
| Somewhat_serious | 114 | 3.2 | 3.3 | 91.5 | 95.1 |
| Very_serious | 33 | 0.9 | 1.0 | 92.4 | 96.1 |
| Dont_know | 131 | 3.7 | 3.8 | 96.1 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 96.1 | 100.0 |
| NA | 138 | 3.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3d2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2927 | 82.3 | 89.0 | 82.3 | 89.0 |
| Somewhat_serious | 179 | 5.0 | 5.4 | 87.3 | 94.4 |
| Very_serious | 29 | 0.8 | 0.9 | 88.1 | 95.3 |
| Dont_know | 153 | 4.3 | 4.7 | 92.4 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.5 | 100.0 |
| NA | 267 | 7.5 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c3d3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 2857 | 80.3 | 87.0 | 80.3 | 87.0 |
| Somewhat_serious | 153 | 4.3 | 4.7 | 84.6 | 91.7 |
| Very_serious | 35 | 1.0 | 1.1 | 85.6 | 92.8 |
| Dont_know | 236 | 6.6 | 7.2 | 92.2 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.3 | 100.0 |
| NA | 274 | 7.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 289 | 90.0 | 92.9 | 90.0 | 92.9 |
| Somewhat_serious | 13 | 4.0 | 4.2 | 94.1 | 97.1 |
| Very_serious | 3 | 0.9 | 1.0 | 95.0 | 98.1 |
| Dont_know | 6 | 1.9 | 1.9 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 10 | 3.1 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 283 | 88.2 | 91.0 | 88.2 | 91.0 |
| Somewhat_serious | 21 | 6.5 | 6.8 | 94.7 | 97.7 |
| Very_serious | 0 | 0.0 | 0.0 | 94.7 | 97.7 |
| Dont_know | 7 | 2.2 | 2.3 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 10 | 3.1 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 278 | 86.6 | 90.0 | 86.6 | 90.0 |
| Somewhat_serious | 14 | 4.4 | 4.5 | 91.0 | 94.5 |
| Very_serious | 1 | 0.3 | 0.3 | 91.3 | 94.8 |
| Dont_know | 16 | 5.0 | 5.2 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 12 | 3.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 188 | 89.5 | 92.2 | 89.5 | 92.2 |
| Somewhat_serious | 10 | 4.8 | 4.9 | 94.3 | 97.1 |
| Very_serious | 0 | 0.0 | 0.0 | 94.3 | 97.1 |
| Dont_know | 6 | 2.9 | 2.9 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 6 | 2.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 176 | 83.8 | 88.0 | 83.8 | 88.0 |
| Somewhat_serious | 15 | 7.1 | 7.5 | 91.0 | 95.5 |
| Very_serious | 1 | 0.5 | 0.5 | 91.4 | 96.0 |
| Dont_know | 8 | 3.8 | 4.0 | 95.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.2 | 100.0 |
| NA | 10 | 4.8 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 177 | 84.3 | 89.4 | 84.3 | 89.4 |
| Somewhat_serious | 6 | 2.9 | 3.0 | 87.1 | 92.4 |
| Very_serious | 3 | 1.4 | 1.5 | 88.6 | 93.9 |
| Dont_know | 12 | 5.7 | 6.1 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 12 | 5.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 277 | 87.9 | 91.4 | 87.9 | 91.4 |
| Somewhat_serious | 8 | 2.5 | 2.6 | 90.5 | 94.1 |
| Very_serious | 5 | 1.6 | 1.7 | 92.1 | 95.7 |
| Dont_know | 13 | 4.1 | 4.3 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 261 | 82.9 | 88.5 | 82.9 | 88.5 |
| Somewhat_serious | 16 | 5.1 | 5.4 | 87.9 | 93.9 |
| Very_serious | 3 | 1.0 | 1.0 | 88.9 | 94.9 |
| Dont_know | 15 | 4.8 | 5.1 | 93.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.7 | 100.0 |
| NA | 20 | 6.3 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 249 | 79.0 | 84.4 | 79.0 | 84.4 |
| Somewhat_serious | 17 | 5.4 | 5.8 | 84.4 | 90.2 |
| Very_serious | 5 | 1.6 | 1.7 | 86.0 | 91.9 |
| Dont_know | 24 | 7.6 | 8.1 | 93.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.7 | 100.0 |
| NA | 20 | 6.3 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 306 | 86.0 | 89.5 | 86.0 | 89.5 |
| Somewhat_serious | 15 | 4.2 | 4.4 | 90.2 | 93.9 |
| Very_serious | 5 | 1.4 | 1.5 | 91.6 | 95.3 |
| Dont_know | 16 | 4.5 | 4.7 | 96.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.1 | 100.0 |
| NA | 14 | 3.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 278 | 78.1 | 85.0 | 78.1 | 85.0 |
| Somewhat_serious | 27 | 7.6 | 8.3 | 85.7 | 93.3 |
| Very_serious | 6 | 1.7 | 1.8 | 87.4 | 95.1 |
| Dont_know | 16 | 4.5 | 4.9 | 91.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.9 | 100.0 |
| NA | 29 | 8.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 264 | 74.2 | 82.2 | 74.2 | 82.2 |
| Somewhat_serious | 27 | 7.6 | 8.4 | 81.7 | 90.7 |
| Very_serious | 6 | 1.7 | 1.9 | 83.4 | 92.5 |
| Dont_know | 24 | 6.7 | 7.5 | 90.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.2 | 100.0 |
| NA | 35 | 9.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 502 | 85.8 | 89.6 | 85.8 | 89.6 |
| Somewhat_serious | 19 | 3.2 | 3.4 | 89.1 | 93.0 |
| Very_serious | 10 | 1.7 | 1.8 | 90.8 | 94.8 |
| Dont_know | 28 | 4.8 | 5.0 | 95.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 95.7 | 100.0 |
| NA | 25 | 4.3 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 459 | 78.5 | 87.6 | 78.5 | 87.6 |
| Somewhat_serious | 28 | 4.8 | 5.3 | 83.2 | 92.9 |
| Very_serious | 8 | 1.4 | 1.5 | 84.6 | 94.5 |
| Dont_know | 28 | 4.8 | 5.3 | 89.4 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 89.6 | 100.0 |
| NA | 61 | 10.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 458 | 78.3 | 87.2 | 78.3 | 87.2 |
| Somewhat_serious | 22 | 3.8 | 4.2 | 82.1 | 91.4 |
| Very_serious | 6 | 1.0 | 1.1 | 83.1 | 92.6 |
| Dont_know | 38 | 6.5 | 7.2 | 89.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 89.7 | 100.0 |
| NA | 60 | 10.3 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1564 | 89.2 | 92.9 | 89.2 | 92.9 |
| Somewhat_serious | 49 | 2.8 | 2.9 | 92.0 | 95.8 |
| Very_serious | 10 | 0.6 | 0.6 | 92.5 | 96.4 |
| Dont_know | 60 | 3.4 | 3.6 | 96.0 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 96.0 | 100.0 |
| NA | 70 | 4.0 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1457 | 83.1 | 90.0 | 83.1 | 90.0 |
| Somewhat_serious | 72 | 4.1 | 4.4 | 87.2 | 94.4 |
| Very_serious | 11 | 0.6 | 0.7 | 87.8 | 95.1 |
| Dont_know | 78 | 4.4 | 4.8 | 92.2 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.3 | 100.0 |
| NA | 135 | 7.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 1418 | 80.8 | 87.5 | 80.8 | 87.5 |
| Somewhat_serious | 67 | 3.8 | 4.1 | 84.7 | 91.6 |
| Very_serious | 14 | 0.8 | 0.9 | 85.5 | 92.5 |
| Dont_know | 121 | 6.9 | 7.5 | 92.4 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 92.4 | 100.0 |
| NA | 133 | 7.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 13 | 81.2 | 86.7 | 81.2 | 86.7 |
| Somewhat_serious | 0 | 0.0 | 0.0 | 81.2 | 86.7 |
| Very_serious | 0 | 0.0 | 0.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 13 | 81.2 | 92.9 | 81.2 | 92.9 |
| Somewhat_serious | 0 | 0.0 | 0.0 | 81.2 | 92.9 |
| Very_serious | 0 | 0.0 | 0.0 | 81.2 | 92.9 |
| Dont_know | 1 | 6.2 | 7.1 | 87.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 87.5 | 100.0 |
| NA | 2 | 12.5 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Non_Minor | 13 | 81.2 | 92.9 | 81.2 | 92.9 |
| Somewhat_serious | 0 | 0.0 | 0.0 | 81.2 | 92.9 |
| Very_serious | 0 | 0.0 | 0.0 | 81.2 | 92.9 |
| Dont_know | 1 | 6.2 | 7.1 | 87.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 87.5 | 100.0 |
| NA | 2 | 12.5 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c4a1 <- as.factor(d[,"c4a1"])
levels(c4a1) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4a1 <- ordered(c4a1, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4a1)
new.d <- apply_labels(new.d, c4a1 = "Talk outside-Current")
temp.d <- data.frame (new.d, c4a1)
c4a2 <- as.factor(d[,"c4a2"])
levels(c4a2) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4a2 <- ordered(c4a2, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4a2)
new.d <- apply_labels(new.d, c4a2 = "Talk outside-age 31 up")
temp.d <- data.frame (new.d, c4a2)
c4a3 <- as.factor(d[,"c4a3"])
levels(c4a3) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4a3 <- ordered(c4a3, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4a3)
new.d <- apply_labels(new.d, c4a3 = "Talk outside-Childhood or young")
temp.d <- data.frame (new.d, c4a3)
result<-questionr::freq(temp.d$c4a1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1283 | 36.1 | 37.0 | 36.1 | 37.0 |
| Sometimes | 1453 | 40.8 | 41.9 | 76.9 | 78.9 |
| Rarely_Never | 672 | 18.9 | 19.4 | 95.8 | 98.2 |
| Dont_know | 61 | 1.7 | 1.8 | 97.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.5 | 100.0 |
| NA | 88 | 2.5 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4a2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1288 | 36.2 | 38.7 | 36.2 | 38.7 |
| Sometimes | 1437 | 40.4 | 43.1 | 76.6 | 81.8 |
| Rarely_Never | 479 | 13.5 | 14.4 | 90.1 | 96.2 |
| Dont_know | 128 | 3.6 | 3.8 | 93.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.7 | 100.0 |
| NA | 225 | 6.3 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4a3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1901 | 53.4 | 57.6 | 53.4 | 57.6 |
| Sometimes | 875 | 24.6 | 26.5 | 78.0 | 84.1 |
| Rarely_Never | 313 | 8.8 | 9.5 | 86.8 | 93.6 |
| Dont_know | 211 | 5.9 | 6.4 | 92.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.8 | 100.0 |
| NA | 257 | 7.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 132 | 41.1 | 41.9 | 41.1 | 41.9 |
| Sometimes | 125 | 38.9 | 39.7 | 80.1 | 81.6 |
| Rarely_Never | 56 | 17.4 | 17.8 | 97.5 | 99.4 |
| Dont_know | 2 | 0.6 | 0.6 | 98.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.1 | 100.0 |
| NA | 6 | 1.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 125 | 38.9 | 40.2 | 38.9 | 40.2 |
| Sometimes | 137 | 42.7 | 44.1 | 81.6 | 84.2 |
| Rarely_Never | 41 | 12.8 | 13.2 | 94.4 | 97.4 |
| Dont_know | 8 | 2.5 | 2.6 | 96.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.9 | 100.0 |
| NA | 10 | 3.1 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 200 | 62.3 | 64.7 | 62.3 | 64.7 |
| Sometimes | 75 | 23.4 | 24.3 | 85.7 | 89.0 |
| Rarely_Never | 22 | 6.9 | 7.1 | 92.5 | 96.1 |
| Dont_know | 12 | 3.7 | 3.9 | 96.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.3 | 100.0 |
| NA | 12 | 3.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 91 | 43.3 | 44.6 | 43.3 | 44.6 |
| Sometimes | 74 | 35.2 | 36.3 | 78.6 | 80.9 |
| Rarely_Never | 37 | 17.6 | 18.1 | 96.2 | 99.0 |
| Dont_know | 2 | 1.0 | 1.0 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 6 | 2.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 91 | 43.3 | 45.3 | 43.3 | 45.3 |
| Sometimes | 81 | 38.6 | 40.3 | 81.9 | 85.6 |
| Rarely_Never | 28 | 13.3 | 13.9 | 95.2 | 99.5 |
| Dont_know | 1 | 0.5 | 0.5 | 95.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.7 | 100.0 |
| NA | 9 | 4.3 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 124 | 59.0 | 62.3 | 59.0 | 62.3 |
| Sometimes | 54 | 25.7 | 27.1 | 84.8 | 89.4 |
| Rarely_Never | 11 | 5.2 | 5.5 | 90.0 | 95.0 |
| Dont_know | 10 | 4.8 | 5.0 | 94.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.8 | 100.0 |
| NA | 11 | 5.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 121 | 38.4 | 39.8 | 38.4 | 39.8 |
| Sometimes | 116 | 36.8 | 38.2 | 75.2 | 78.0 |
| Rarely_Never | 63 | 20.0 | 20.7 | 95.2 | 98.7 |
| Dont_know | 4 | 1.3 | 1.3 | 96.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.5 | 100.0 |
| NA | 11 | 3.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 106 | 33.7 | 35.8 | 33.7 | 35.8 |
| Sometimes | 132 | 41.9 | 44.6 | 75.6 | 80.4 |
| Rarely_Never | 43 | 13.7 | 14.5 | 89.2 | 94.9 |
| Dont_know | 15 | 4.8 | 5.1 | 94.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.0 | 100.0 |
| NA | 19 | 6.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 168 | 53.3 | 57.3 | 53.3 | 57.3 |
| Sometimes | 72 | 22.9 | 24.6 | 76.2 | 81.9 |
| Rarely_Never | 31 | 9.8 | 10.6 | 86.0 | 92.5 |
| Dont_know | 22 | 7.0 | 7.5 | 93.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.0 | 100.0 |
| NA | 22 | 7.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 153 | 43.0 | 44.7 | 43.0 | 44.7 |
| Sometimes | 144 | 40.4 | 42.1 | 83.4 | 86.8 |
| Rarely_Never | 38 | 10.7 | 11.1 | 94.1 | 98.0 |
| Dont_know | 7 | 2.0 | 2.0 | 96.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.1 | 100.0 |
| NA | 14 | 3.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 143 | 40.2 | 43.1 | 40.2 | 43.1 |
| Sometimes | 144 | 40.4 | 43.4 | 80.6 | 86.4 |
| Rarely_Never | 32 | 9.0 | 9.6 | 89.6 | 96.1 |
| Dont_know | 13 | 3.7 | 3.9 | 93.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.3 | 100.0 |
| NA | 24 | 6.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 196 | 55.1 | 60.9 | 55.1 | 60.9 |
| Sometimes | 87 | 24.4 | 27.0 | 79.5 | 87.9 |
| Rarely_Never | 15 | 4.2 | 4.7 | 83.7 | 92.5 |
| Dont_know | 24 | 6.7 | 7.5 | 90.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.4 | 100.0 |
| NA | 34 | 9.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 232 | 39.7 | 40.5 | 39.7 | 40.5 |
| Sometimes | 223 | 38.1 | 38.9 | 77.8 | 79.4 |
| Rarely_Never | 102 | 17.4 | 17.8 | 95.2 | 97.2 |
| Dont_know | 16 | 2.7 | 2.8 | 97.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.9 | 100.0 |
| NA | 12 | 2.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 240 | 41.0 | 45.1 | 41.0 | 45.1 |
| Sometimes | 189 | 32.3 | 35.5 | 73.3 | 80.6 |
| Rarely_Never | 80 | 13.7 | 15.0 | 87.0 | 95.7 |
| Dont_know | 23 | 3.9 | 4.3 | 90.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.9 | 100.0 |
| NA | 53 | 9.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 310 | 53.0 | 58.3 | 53.0 | 58.3 |
| Sometimes | 131 | 22.4 | 24.6 | 75.4 | 82.9 |
| Rarely_Never | 54 | 9.2 | 10.2 | 84.6 | 93.0 |
| Dont_know | 37 | 6.3 | 7.0 | 90.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.9 | 100.0 |
| NA | 53 | 9.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 548 | 31.2 | 32.0 | 31.2 | 32.0 |
| Sometimes | 763 | 43.5 | 44.5 | 74.7 | 76.4 |
| Rarely_Never | 374 | 21.3 | 21.8 | 96.1 | 98.3 |
| Dont_know | 30 | 1.7 | 1.7 | 97.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.8 | 100.0 |
| NA | 39 | 2.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 580 | 33.1 | 35.3 | 33.1 | 35.3 |
| Sometimes | 744 | 42.4 | 45.2 | 75.5 | 80.5 |
| Rarely_Never | 253 | 14.4 | 15.4 | 89.9 | 95.9 |
| Dont_know | 68 | 3.9 | 4.1 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 109 | 6.2 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 895 | 51.0 | 54.9 | 51.0 | 54.9 |
| Sometimes | 451 | 25.7 | 27.7 | 76.7 | 82.6 |
| Rarely_Never | 179 | 10.2 | 11.0 | 86.9 | 93.6 |
| Dont_know | 105 | 6.0 | 6.4 | 92.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.9 | 100.0 |
| NA | 124 | 7.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 6 | 37.5 | 37.5 | 37.5 | 37.5 |
| Sometimes | 8 | 50.0 | 50.0 | 87.5 | 87.5 |
| Rarely_Never | 2 | 12.5 | 12.5 | 100.0 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 3 | 18.8 | 20.0 | 18.8 | 20.0 |
| Sometimes | 10 | 62.5 | 66.7 | 81.2 | 86.7 |
| Rarely_Never | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 8 | 50.0 | 53.3 | 50.0 | 53.3 |
| Sometimes | 5 | 31.2 | 33.3 | 81.2 | 86.7 |
| Rarely_Never | 1 | 6.2 | 6.7 | 87.5 | 93.3 |
| Dont_know | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c4b1 <- as.factor(d[,"c4b1"])
levels(c4b1) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4b1 <- ordered(c4b1, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4b1)
new.d <- apply_labels(new.d, c4b1 = "watch out-Current")
temp.d <- data.frame (new.d, c4b1)
c4b2 <- as.factor(d[,"c4b2"])
levels(c4b2) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4b2 <- ordered(c4b2, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4b2)
new.d <- apply_labels(new.d, c4b2 = "watch out-age 31 up")
temp.d <- data.frame (new.d, c4b2)
c4b3 <- as.factor(d[,"c4b3"])
levels(c4b3) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4b3 <- ordered(c4b3, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4b3)
new.d <- apply_labels(new.d, c4b3 = "watch out-Childhood or young")
temp.d <- data.frame (new.d, c4b3)
result<-questionr::freq(temp.d$c4b1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1604 | 45.1 | 47.1 | 45.1 | 47.1 |
| Sometimes | 1062 | 29.9 | 31.2 | 75.0 | 78.3 |
| Rarely_Never | 498 | 14.0 | 14.6 | 89.0 | 92.9 |
| Dont_know | 241 | 6.8 | 7.1 | 95.7 | 100.0 |
| Scantron_Error | 1 | 0.0 | 0.0 | 95.8 | 100.0 |
| NA | 151 | 4.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4b2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1381 | 38.8 | 42.2 | 38.8 | 42.2 |
| Sometimes | 1189 | 33.4 | 36.3 | 72.3 | 78.6 |
| Rarely_Never | 467 | 13.1 | 14.3 | 85.4 | 92.8 |
| Dont_know | 231 | 6.5 | 7.1 | 91.9 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 92.0 | 100.0 |
| NA | 286 | 8.0 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4b3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1891 | 53.2 | 58.3 | 53.2 | 58.3 |
| Sometimes | 756 | 21.3 | 23.3 | 74.4 | 81.6 |
| Rarely_Never | 302 | 8.5 | 9.3 | 82.9 | 91.0 |
| Dont_know | 291 | 8.2 | 9.0 | 91.1 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 91.1 | 100.0 |
| NA | 315 | 8.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 119 | 37.1 | 37.9 | 37.1 | 37.9 |
| Sometimes | 118 | 36.8 | 37.6 | 73.8 | 75.5 |
| Rarely_Never | 50 | 15.6 | 15.9 | 89.4 | 91.4 |
| Dont_know | 27 | 8.4 | 8.6 | 97.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.8 | 100.0 |
| NA | 7 | 2.2 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 106 | 33.0 | 34.4 | 33.0 | 34.4 |
| Sometimes | 140 | 43.6 | 45.5 | 76.6 | 79.9 |
| Rarely_Never | 43 | 13.4 | 14.0 | 90.0 | 93.8 |
| Dont_know | 19 | 5.9 | 6.2 | 96.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.0 | 100.0 |
| NA | 13 | 4.0 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 189 | 58.9 | 61.8 | 58.9 | 61.8 |
| Sometimes | 71 | 22.1 | 23.2 | 81.0 | 85.0 |
| Rarely_Never | 22 | 6.9 | 7.2 | 87.9 | 92.2 |
| Dont_know | 23 | 7.2 | 7.5 | 95.0 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 95.3 | 100.0 |
| NA | 15 | 4.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 93 | 44.3 | 46.5 | 44.3 | 46.5 |
| Sometimes | 57 | 27.1 | 28.5 | 71.4 | 75.0 |
| Rarely_Never | 38 | 18.1 | 19.0 | 89.5 | 94.0 |
| Dont_know | 12 | 5.7 | 6.0 | 95.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.2 | 100.0 |
| NA | 10 | 4.8 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 83 | 39.5 | 42.3 | 39.5 | 42.3 |
| Sometimes | 64 | 30.5 | 32.7 | 70.0 | 75.0 |
| Rarely_Never | 38 | 18.1 | 19.4 | 88.1 | 94.4 |
| Dont_know | 11 | 5.2 | 5.6 | 93.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.3 | 100.0 |
| NA | 14 | 6.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 112 | 53.3 | 57.4 | 53.3 | 57.4 |
| Sometimes | 42 | 20.0 | 21.5 | 73.3 | 79.0 |
| Rarely_Never | 25 | 11.9 | 12.8 | 85.2 | 91.8 |
| Dont_know | 16 | 7.6 | 8.2 | 92.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.9 | 100.0 |
| NA | 15 | 7.1 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 129 | 41.0 | 43.1 | 41.0 | 43.1 |
| Sometimes | 94 | 29.8 | 31.4 | 70.8 | 74.6 |
| Rarely_Never | 50 | 15.9 | 16.7 | 86.7 | 91.3 |
| Dont_know | 26 | 8.3 | 8.7 | 94.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.9 | 100.0 |
| NA | 16 | 5.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 95 | 30.2 | 32.8 | 30.2 | 32.8 |
| Sometimes | 104 | 33.0 | 35.9 | 63.2 | 68.6 |
| Rarely_Never | 58 | 18.4 | 20.0 | 81.6 | 88.6 |
| Dont_know | 33 | 10.5 | 11.4 | 92.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.1 | 100.0 |
| NA | 25 | 7.9 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 127 | 40.3 | 44.3 | 40.3 | 44.3 |
| Sometimes | 83 | 26.3 | 28.9 | 66.7 | 73.2 |
| Rarely_Never | 35 | 11.1 | 12.2 | 77.8 | 85.4 |
| Dont_know | 42 | 13.3 | 14.6 | 91.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.1 | 100.0 |
| NA | 28 | 8.9 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 162 | 45.5 | 47.9 | 45.5 | 47.9 |
| Sometimes | 114 | 32.0 | 33.7 | 77.5 | 81.7 |
| Rarely_Never | 39 | 11.0 | 11.5 | 88.5 | 93.2 |
| Dont_know | 23 | 6.5 | 6.8 | 94.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.9 | 100.0 |
| NA | 18 | 5.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 143 | 40.2 | 43.9 | 40.2 | 43.9 |
| Sometimes | 127 | 35.7 | 39.0 | 75.8 | 82.8 |
| Rarely_Never | 38 | 10.7 | 11.7 | 86.5 | 94.5 |
| Dont_know | 18 | 5.1 | 5.5 | 91.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.6 | 100.0 |
| NA | 30 | 8.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 193 | 54.2 | 60.7 | 54.2 | 60.7 |
| Sometimes | 78 | 21.9 | 24.5 | 76.1 | 85.2 |
| Rarely_Never | 22 | 6.2 | 6.9 | 82.3 | 92.1 |
| Dont_know | 25 | 7.0 | 7.9 | 89.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 89.3 | 100.0 |
| NA | 38 | 10.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 287 | 49.1 | 51.4 | 49.1 | 51.4 |
| Sometimes | 167 | 28.5 | 29.9 | 77.6 | 81.4 |
| Rarely_Never | 77 | 13.2 | 13.8 | 90.8 | 95.2 |
| Dont_know | 26 | 4.4 | 4.7 | 95.2 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 95.4 | 100.0 |
| NA | 27 | 4.6 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 251 | 42.9 | 48.3 | 42.9 | 48.3 |
| Sometimes | 167 | 28.5 | 32.1 | 71.5 | 80.4 |
| Rarely_Never | 70 | 12.0 | 13.5 | 83.4 | 93.8 |
| Dont_know | 31 | 5.3 | 6.0 | 88.7 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 88.9 | 100.0 |
| NA | 65 | 11.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 313 | 53.5 | 60.3 | 53.5 | 60.3 |
| Sometimes | 115 | 19.7 | 22.2 | 73.2 | 82.5 |
| Rarely_Never | 52 | 8.9 | 10.0 | 82.1 | 92.5 |
| Dont_know | 38 | 6.5 | 7.3 | 88.5 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 88.7 | 100.0 |
| NA | 66 | 11.3 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 809 | 46.1 | 48.1 | 46.1 | 48.1 |
| Sometimes | 504 | 28.7 | 30.0 | 74.9 | 78.1 |
| Rarely_Never | 243 | 13.9 | 14.4 | 88.7 | 92.5 |
| Dont_know | 126 | 7.2 | 7.5 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 72 | 4.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 700 | 39.9 | 43.3 | 39.9 | 43.3 |
| Sometimes | 580 | 33.1 | 35.9 | 73.0 | 79.2 |
| Rarely_Never | 218 | 12.4 | 13.5 | 85.4 | 92.7 |
| Dont_know | 116 | 6.6 | 7.2 | 92.0 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.1 | 100.0 |
| NA | 138 | 7.9 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 950 | 54.2 | 59.3 | 54.2 | 59.3 |
| Sometimes | 362 | 20.6 | 22.6 | 74.8 | 81.9 |
| Rarely_Never | 146 | 8.3 | 9.1 | 83.1 | 91.0 |
| Dont_know | 144 | 8.2 | 9.0 | 91.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.3 | 100.0 |
| NA | 152 | 8.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 5 | 31.2 | 33.3 | 31.2 | 33.3 |
| Sometimes | 8 | 50.0 | 53.3 | 81.2 | 86.7 |
| Rarely_Never | 1 | 6.2 | 6.7 | 87.5 | 93.3 |
| Dont_know | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 3 | 18.8 | 20.0 | 18.8 | 20.0 |
| Sometimes | 7 | 43.8 | 46.7 | 62.5 | 66.7 |
| Rarely_Never | 2 | 12.5 | 13.3 | 75.0 | 80.0 |
| Dont_know | 3 | 18.8 | 20.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 7 | 43.8 | 46.7 | 43.8 | 46.7 |
| Sometimes | 5 | 31.2 | 33.3 | 75.0 | 80.0 |
| Rarely_Never | 0 | 0.0 | 0.0 | 75.0 | 80.0 |
| Dont_know | 3 | 18.8 | 20.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c4c1 <- as.factor(d[,"c4c1"])
levels(c4c1) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4c1 <- ordered(c4c1, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4c1)
new.d <- apply_labels(new.d, c4c1 = "Know names-Current")
temp.d <- data.frame (new.d, c4c1)
c4c2 <- as.factor(d[,"c4c2"])
levels(c4c2) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4c2 <- ordered(c4c2, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4c2)
new.d <- apply_labels(new.d, c4c2 = "Know names-age 31 up")
temp.d <- data.frame (new.d, c4c2)
c4c3 <- as.factor(d[,"c4c3"])
levels(c4c3) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4c3 <- ordered(c4c3, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4c3)
new.d <- apply_labels(new.d, c4c3 = "Know names-Childhood or young")
temp.d <- data.frame (new.d, c4c3)
result<-questionr::freq(temp.d$c4c1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 998 | 28.1 | 29.5 | 28.1 | 29.5 |
| Sometimes | 1378 | 38.7 | 40.7 | 66.8 | 70.2 |
| Rarely_Never | 944 | 26.5 | 27.9 | 93.3 | 98.1 |
| Dont_know | 62 | 1.7 | 1.8 | 95.1 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 95.1 | 100.0 |
| NA | 173 | 4.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4c2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1053 | 29.6 | 32.6 | 29.6 | 32.6 |
| Sometimes | 1383 | 38.9 | 42.8 | 68.5 | 75.4 |
| Rarely_Never | 699 | 19.7 | 21.6 | 88.1 | 97.0 |
| Dont_know | 94 | 2.6 | 2.9 | 90.8 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 90.8 | 100.0 |
| NA | 326 | 9.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4c3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1933 | 54.3 | 60.3 | 54.3 | 60.3 |
| Sometimes | 766 | 21.5 | 23.9 | 75.9 | 84.1 |
| Rarely_Never | 361 | 10.1 | 11.3 | 86.0 | 95.4 |
| Dont_know | 146 | 4.1 | 4.6 | 90.1 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 90.2 | 100.0 |
| NA | 349 | 9.8 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 74 | 23.1 | 24.0 | 23.1 | 24.0 |
| Sometimes | 133 | 41.4 | 43.2 | 64.5 | 67.2 |
| Rarely_Never | 97 | 30.2 | 31.5 | 94.7 | 98.7 |
| Dont_know | 4 | 1.2 | 1.3 | 96.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.0 | 100.0 |
| NA | 13 | 4.0 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 85 | 26.5 | 28.1 | 26.5 | 28.1 |
| Sometimes | 141 | 43.9 | 46.5 | 70.4 | 74.6 |
| Rarely_Never | 75 | 23.4 | 24.8 | 93.8 | 99.3 |
| Dont_know | 2 | 0.6 | 0.7 | 94.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.4 | 100.0 |
| NA | 18 | 5.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 194 | 60.4 | 64.7 | 60.4 | 64.7 |
| Sometimes | 62 | 19.3 | 20.7 | 79.8 | 85.3 |
| Rarely_Never | 35 | 10.9 | 11.7 | 90.7 | 97.0 |
| Dont_know | 9 | 2.8 | 3.0 | 93.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.5 | 100.0 |
| NA | 21 | 6.5 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 60 | 28.6 | 29.6 | 28.6 | 29.6 |
| Sometimes | 86 | 41.0 | 42.4 | 69.5 | 71.9 |
| Rarely_Never | 51 | 24.3 | 25.1 | 93.8 | 97.0 |
| Dont_know | 6 | 2.9 | 3.0 | 96.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.7 | 100.0 |
| NA | 7 | 3.3 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 58 | 27.6 | 29.3 | 27.6 | 29.3 |
| Sometimes | 95 | 45.2 | 48.0 | 72.9 | 77.3 |
| Rarely_Never | 41 | 19.5 | 20.7 | 92.4 | 98.0 |
| Dont_know | 4 | 1.9 | 2.0 | 94.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.3 | 100.0 |
| NA | 12 | 5.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 121 | 57.6 | 61.7 | 57.6 | 61.7 |
| Sometimes | 47 | 22.4 | 24.0 | 80.0 | 85.7 |
| Rarely_Never | 17 | 8.1 | 8.7 | 88.1 | 94.4 |
| Dont_know | 11 | 5.2 | 5.6 | 93.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.3 | 100.0 |
| NA | 14 | 6.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 80 | 25.4 | 27.1 | 25.4 | 27.1 |
| Sometimes | 114 | 36.2 | 38.6 | 61.6 | 65.8 |
| Rarely_Never | 100 | 31.7 | 33.9 | 93.3 | 99.7 |
| Dont_know | 1 | 0.3 | 0.3 | 93.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.7 | 100.0 |
| NA | 20 | 6.3 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 72 | 22.9 | 25.4 | 22.9 | 25.4 |
| Sometimes | 116 | 36.8 | 41.0 | 59.7 | 66.4 |
| Rarely_Never | 82 | 26.0 | 29.0 | 85.7 | 95.4 |
| Dont_know | 13 | 4.1 | 4.6 | 89.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 89.8 | 100.0 |
| NA | 32 | 10.2 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 160 | 50.8 | 56.3 | 50.8 | 56.3 |
| Sometimes | 70 | 22.2 | 24.6 | 73.0 | 81.0 |
| Rarely_Never | 37 | 11.7 | 13.0 | 84.8 | 94.0 |
| Dont_know | 17 | 5.4 | 6.0 | 90.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.2 | 100.0 |
| NA | 31 | 9.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 94 | 26.4 | 28.1 | 26.4 | 28.1 |
| Sometimes | 143 | 40.2 | 42.7 | 66.6 | 70.7 |
| Rarely_Never | 93 | 26.1 | 27.8 | 92.7 | 98.5 |
| Dont_know | 5 | 1.4 | 1.5 | 94.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.1 | 100.0 |
| NA | 21 | 5.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 114 | 32.0 | 35.5 | 32.0 | 35.5 |
| Sometimes | 132 | 37.1 | 41.1 | 69.1 | 76.6 |
| Rarely_Never | 66 | 18.5 | 20.6 | 87.6 | 97.2 |
| Dont_know | 9 | 2.5 | 2.8 | 90.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.2 | 100.0 |
| NA | 35 | 9.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 179 | 50.3 | 57.6 | 50.3 | 57.6 |
| Sometimes | 76 | 21.3 | 24.4 | 71.6 | 82.0 |
| Rarely_Never | 40 | 11.2 | 12.9 | 82.9 | 94.9 |
| Dont_know | 15 | 4.2 | 4.8 | 87.1 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 87.4 | 100.0 |
| NA | 45 | 12.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 222 | 37.9 | 39.7 | 37.9 | 39.7 |
| Sometimes | 209 | 35.7 | 37.4 | 73.7 | 77.1 |
| Rarely_Never | 112 | 19.1 | 20.0 | 92.8 | 97.1 |
| Dont_know | 15 | 2.6 | 2.7 | 95.4 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 95.6 | 100.0 |
| NA | 26 | 4.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 213 | 36.4 | 41.1 | 36.4 | 41.1 |
| Sometimes | 222 | 37.9 | 42.9 | 74.4 | 84.0 |
| Rarely_Never | 68 | 11.6 | 13.1 | 86.0 | 97.1 |
| Dont_know | 14 | 2.4 | 2.7 | 88.4 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 88.5 | 100.0 |
| NA | 67 | 11.5 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 314 | 53.7 | 60.5 | 53.7 | 60.5 |
| Sometimes | 126 | 21.5 | 24.3 | 75.2 | 84.8 |
| Rarely_Never | 57 | 9.7 | 11.0 | 85.0 | 95.8 |
| Dont_know | 21 | 3.6 | 4.0 | 88.5 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 88.7 | 100.0 |
| NA | 66 | 11.3 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 463 | 26.4 | 27.7 | 26.4 | 27.7 |
| Sometimes | 688 | 39.2 | 41.2 | 65.6 | 69.0 |
| Rarely_Never | 488 | 27.8 | 29.2 | 93.4 | 98.2 |
| Dont_know | 29 | 1.7 | 1.7 | 95.1 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 95.2 | 100.0 |
| NA | 85 | 4.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 508 | 29.0 | 31.8 | 29.0 | 31.8 |
| Sometimes | 671 | 38.3 | 42.1 | 67.2 | 73.9 |
| Rarely_Never | 364 | 20.8 | 22.8 | 88.0 | 96.7 |
| Dont_know | 51 | 2.9 | 3.2 | 90.9 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 90.9 | 100.0 |
| NA | 159 | 9.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 959 | 54.7 | 60.5 | 54.7 | 60.5 |
| Sometimes | 379 | 21.6 | 23.9 | 76.3 | 84.4 |
| Rarely_Never | 175 | 10.0 | 11.0 | 86.3 | 95.5 |
| Dont_know | 72 | 4.1 | 4.5 | 90.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.4 | 100.0 |
| NA | 169 | 9.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 5 | 31.2 | 33.3 | 31.2 | 33.3 |
| Sometimes | 5 | 31.2 | 33.3 | 62.5 | 66.7 |
| Rarely_Never | 3 | 18.8 | 20.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 3 | 18.8 | 23.1 | 18.8 | 23.1 |
| Sometimes | 6 | 37.5 | 46.2 | 56.2 | 69.2 |
| Rarely_Never | 3 | 18.8 | 23.1 | 75.0 | 92.3 |
| Dont_know | 1 | 6.2 | 7.7 | 81.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 81.2 | 100.0 |
| NA | 3 | 18.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 6 | 37.5 | 46.2 | 37.5 | 46.2 |
| Sometimes | 6 | 37.5 | 46.2 | 75.0 | 92.3 |
| Rarely_Never | 0 | 0.0 | 0.0 | 75.0 | 92.3 |
| Dont_know | 1 | 6.2 | 7.7 | 81.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 81.2 | 100.0 |
| NA | 3 | 18.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c4d1 <- as.factor(d[,"c4d1"])
levels(c4d1) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4d1 <- ordered(c4d1, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4d1)
new.d <- apply_labels(new.d, c4d1 = "Know names-Current")
temp.d <- data.frame (new.d, c4d1)
c4d2 <- as.factor(d[,"c4d2"])
levels(c4d2) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4d2 <- ordered(c4d2, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4d2)
new.d <- apply_labels(new.d, c4d2 = "Know names-age 31 up")
temp.d <- data.frame (new.d, c4d2)
c4d3 <- as.factor(d[,"c4d3"])
levels(c4d3) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4d3 <- ordered(c4d3, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4d3)
new.d <- apply_labels(new.d, c4d3 = "Know names-Childhood or young")
temp.d <- data.frame (new.d, c4d3)
result<-questionr::freq(temp.d$c4d1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 463 | 13.0 | 13.6 | 13.0 | 13.6 |
| Sometimes | 1249 | 35.1 | 36.8 | 48.1 | 50.5 |
| Rarely_Never | 1617 | 45.5 | 47.7 | 93.6 | 98.1 |
| Dont_know | 61 | 1.7 | 1.8 | 95.3 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 95.4 | 100.0 |
| NA | 164 | 4.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4d2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 588 | 16.5 | 18.1 | 16.5 | 18.1 |
| Sometimes | 1418 | 39.9 | 43.6 | 56.4 | 61.7 |
| Rarely_Never | 1132 | 31.8 | 34.8 | 88.2 | 96.5 |
| Dont_know | 112 | 3.1 | 3.4 | 91.4 | 100.0 |
| Scantron_Error | 1 | 0.0 | 0.0 | 91.4 | 100.0 |
| NA | 306 | 8.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4d3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1418 | 39.9 | 43.9 | 39.9 | 43.9 |
| Sometimes | 987 | 27.7 | 30.5 | 67.6 | 74.4 |
| Rarely_Never | 631 | 17.7 | 19.5 | 85.4 | 94.0 |
| Dont_know | 194 | 5.5 | 6.0 | 90.8 | 100.0 |
| Scantron_Error | 1 | 0.0 | 0.0 | 90.8 | 100.0 |
| NA | 326 | 9.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 37 | 11.5 | 11.9 | 11.5 | 11.9 |
| Sometimes | 117 | 36.4 | 37.5 | 48.0 | 49.4 |
| Rarely_Never | 153 | 47.7 | 49.0 | 95.6 | 98.4 |
| Dont_know | 5 | 1.6 | 1.6 | 97.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.2 | 100.0 |
| NA | 9 | 2.8 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 53 | 16.5 | 17.2 | 16.5 | 17.2 |
| Sometimes | 133 | 41.4 | 43.2 | 57.9 | 60.4 |
| Rarely_Never | 116 | 36.1 | 37.7 | 94.1 | 98.1 |
| Dont_know | 6 | 1.9 | 1.9 | 96.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.0 | 100.0 |
| NA | 13 | 4.0 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 163 | 50.8 | 53.3 | 50.8 | 53.3 |
| Sometimes | 83 | 25.9 | 27.1 | 76.6 | 80.4 |
| Rarely_Never | 43 | 13.4 | 14.1 | 90.0 | 94.4 |
| Dont_know | 17 | 5.3 | 5.6 | 95.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.3 | 100.0 |
| NA | 15 | 4.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 35 | 16.7 | 17.5 | 16.7 | 17.5 |
| Sometimes | 67 | 31.9 | 33.5 | 48.6 | 51.0 |
| Rarely_Never | 95 | 45.2 | 47.5 | 93.8 | 98.5 |
| Dont_know | 3 | 1.4 | 1.5 | 95.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.2 | 100.0 |
| NA | 10 | 4.8 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 43 | 20.5 | 21.9 | 20.5 | 21.9 |
| Sometimes | 79 | 37.6 | 40.3 | 58.1 | 62.2 |
| Rarely_Never | 71 | 33.8 | 36.2 | 91.9 | 98.5 |
| Dont_know | 3 | 1.4 | 1.5 | 93.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.3 | 100.0 |
| NA | 14 | 6.7 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 87 | 41.4 | 44.8 | 41.4 | 44.8 |
| Sometimes | 62 | 29.5 | 32.0 | 71.0 | 76.8 |
| Rarely_Never | 35 | 16.7 | 18.0 | 87.6 | 94.8 |
| Dont_know | 10 | 4.8 | 5.2 | 92.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.4 | 100.0 |
| NA | 16 | 7.6 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 47 | 14.9 | 15.5 | 14.9 | 15.5 |
| Sometimes | 110 | 34.9 | 36.3 | 49.8 | 51.8 |
| Rarely_Never | 143 | 45.4 | 47.2 | 95.2 | 99.0 |
| Dont_know | 3 | 1.0 | 1.0 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 38 | 12.1 | 13.1 | 12.1 | 13.1 |
| Sometimes | 119 | 37.8 | 40.9 | 49.8 | 54.0 |
| Rarely_Never | 119 | 37.8 | 40.9 | 87.6 | 94.8 |
| Dont_know | 15 | 4.8 | 5.2 | 92.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.4 | 100.0 |
| NA | 24 | 7.6 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 116 | 36.8 | 39.6 | 36.8 | 39.6 |
| Sometimes | 99 | 31.4 | 33.8 | 68.3 | 73.4 |
| Rarely_Never | 58 | 18.4 | 19.8 | 86.7 | 93.2 |
| Dont_know | 20 | 6.3 | 6.8 | 93.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.0 | 100.0 |
| NA | 22 | 7.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 48 | 13.5 | 14.2 | 13.5 | 14.2 |
| Sometimes | 140 | 39.3 | 41.4 | 52.8 | 55.6 |
| Rarely_Never | 140 | 39.3 | 41.4 | 92.1 | 97.0 |
| Dont_know | 10 | 2.8 | 3.0 | 94.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.9 | 100.0 |
| NA | 18 | 5.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 62 | 17.4 | 19.3 | 17.4 | 19.3 |
| Sometimes | 162 | 45.5 | 50.5 | 62.9 | 69.8 |
| Rarely_Never | 83 | 23.3 | 25.9 | 86.2 | 95.6 |
| Dont_know | 14 | 3.9 | 4.4 | 90.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.2 | 100.0 |
| NA | 35 | 9.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 135 | 37.9 | 42.9 | 37.9 | 42.9 |
| Sometimes | 93 | 26.1 | 29.5 | 64.0 | 72.4 |
| Rarely_Never | 63 | 17.7 | 20.0 | 81.7 | 92.4 |
| Dont_know | 24 | 6.7 | 7.6 | 88.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 88.5 | 100.0 |
| NA | 41 | 11.5 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 106 | 18.1 | 19.2 | 18.1 | 19.2 |
| Sometimes | 217 | 37.1 | 39.3 | 55.2 | 58.5 |
| Rarely_Never | 216 | 36.9 | 39.1 | 92.1 | 97.6 |
| Dont_know | 11 | 1.9 | 2.0 | 94.0 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 94.4 | 100.0 |
| NA | 33 | 5.6 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 121 | 20.7 | 23.4 | 20.7 | 23.4 |
| Sometimes | 230 | 39.3 | 44.4 | 60.0 | 67.8 |
| Rarely_Never | 149 | 25.5 | 28.8 | 85.5 | 96.5 |
| Dont_know | 17 | 2.9 | 3.3 | 88.4 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 88.5 | 100.0 |
| NA | 67 | 11.5 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 230 | 39.3 | 44.7 | 39.3 | 44.7 |
| Sometimes | 163 | 27.9 | 31.7 | 67.2 | 76.5 |
| Rarely_Never | 97 | 16.6 | 18.9 | 83.8 | 95.3 |
| Dont_know | 23 | 3.9 | 4.5 | 87.7 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 87.9 | 100.0 |
| NA | 71 | 12.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 183 | 10.4 | 10.9 | 10.4 | 10.9 |
| Sometimes | 593 | 33.8 | 35.5 | 44.2 | 46.4 |
| Rarely_Never | 866 | 49.4 | 51.8 | 93.6 | 98.2 |
| Dont_know | 29 | 1.7 | 1.7 | 95.3 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 95.3 | 100.0 |
| NA | 82 | 4.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 266 | 15.2 | 16.6 | 15.2 | 16.6 |
| Sometimes | 689 | 39.3 | 43.0 | 54.4 | 59.6 |
| Rarely_Never | 590 | 33.6 | 36.8 | 88.1 | 96.4 |
| Dont_know | 57 | 3.2 | 3.6 | 91.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.3 | 100.0 |
| NA | 152 | 8.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 678 | 38.7 | 42.5 | 38.7 | 42.5 |
| Sometimes | 482 | 27.5 | 30.2 | 66.1 | 72.8 |
| Rarely_Never | 334 | 19.0 | 21.0 | 85.2 | 93.7 |
| Dont_know | 100 | 5.7 | 6.3 | 90.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.9 | 100.0 |
| NA | 160 | 9.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 7 | 43.8 | 43.8 | 43.8 | 43.8 |
| Sometimes | 5 | 31.2 | 31.2 | 75.0 | 75.0 |
| Rarely_Never | 4 | 25.0 | 25.0 | 100.0 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 5 | 31.2 | 33.3 | 31.2 | 33.3 |
| Sometimes | 6 | 37.5 | 40.0 | 68.8 | 73.3 |
| Rarely_Never | 4 | 25.0 | 26.7 | 93.8 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 9 | 56.2 | 60.0 | 56.2 | 60.0 |
| Sometimes | 5 | 31.2 | 33.3 | 87.5 | 93.3 |
| Rarely_Never | 1 | 6.2 | 6.7 | 93.8 | 100.0 |
| Dont_know | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
c4e1 <- as.factor(d[,"c4e1"])
levels(c4e1) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4e1 <- ordered(c4e1, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4e1)
new.d <- apply_labels(new.d, c4e1 = "ask for help-Current")
temp.d <- data.frame (new.d, c4e1)
c4e2 <- as.factor(d[,"c4e2"])
levels(c4e2) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4e2 <- ordered(c4e2, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4e2)
new.d <- apply_labels(new.d, c4e2 = "ask for help-age 31 up")
temp.d <- data.frame (new.d, c4e2)
c4e3 <- as.factor(d[,"c4e3"])
levels(c4e3) <- list(Often="1",
Sometimes="2",
Rarely_Never="3",
Dont_know="88",
Scantron_Error="*")
c4e3 <- ordered(c4e3, c("Often", "Sometimes", "Rarely_Never", "Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, c4e3)
new.d <- apply_labels(new.d, c4e3 = "ask for help-Childhood or young")
temp.d <- data.frame (new.d, c4e3)
result<-questionr::freq(temp.d$c4e1, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "1. Current (from prostate cancer diagnosis to present)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 562 | 15.8 | 17.1 | 15.8 | 17.1 |
| Sometimes | 1104 | 31.0 | 33.5 | 46.8 | 50.6 |
| Rarely_Never | 1327 | 37.3 | 40.3 | 84.1 | 90.9 |
| Dont_know | 296 | 8.3 | 9.0 | 92.5 | 99.9 |
| Scantron_Error | 4 | 0.1 | 0.1 | 92.6 | 100.0 |
| NA | 264 | 7.4 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4e2, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 613 | 17.2 | 19.4 | 17.2 | 19.4 |
| Sometimes | 1186 | 33.3 | 37.6 | 50.6 | 57.0 |
| Rarely_Never | 1087 | 30.6 | 34.4 | 81.1 | 91.4 |
| Dont_know | 270 | 7.6 | 8.5 | 88.7 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 88.8 | 100.0 |
| NA | 399 | 11.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$c4e3, cum = TRUE ,total = TRUE)
kable(result, format = "simple", align = 'l',caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1253 | 35.2 | 39.8 | 35.2 | 39.8 |
| Sometimes | 947 | 26.6 | 30.1 | 61.8 | 69.8 |
| Rarely_Never | 641 | 18.0 | 20.3 | 79.9 | 90.2 |
| Dont_know | 307 | 8.6 | 9.7 | 88.5 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 88.6 | 100.0 |
| NA | 407 | 11.4 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 39 | 12.1 | 12.8 | 12.1 | 12.8 |
| Sometimes | 105 | 32.7 | 34.4 | 44.9 | 47.2 |
| Rarely_Never | 141 | 43.9 | 46.2 | 88.8 | 93.4 |
| Dont_know | 20 | 6.2 | 6.6 | 95.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.0 | 100.0 |
| NA | 16 | 5.0 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 43 | 13.4 | 14.2 | 13.4 | 14.2 |
| Sometimes | 135 | 42.1 | 44.7 | 55.5 | 58.9 |
| Rarely_Never | 107 | 33.3 | 35.4 | 88.8 | 94.4 |
| Dont_know | 16 | 5.0 | 5.3 | 93.8 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 94.1 | 100.0 |
| NA | 19 | 5.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 139 | 43.3 | 46.2 | 43.3 | 46.2 |
| Sometimes | 88 | 27.4 | 29.2 | 70.7 | 75.4 |
| Rarely_Never | 51 | 15.9 | 16.9 | 86.6 | 92.4 |
| Dont_know | 23 | 7.2 | 7.6 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 20 | 6.2 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 38 | 18.1 | 19.3 | 18.1 | 19.3 |
| Sometimes | 61 | 29.0 | 31.0 | 47.1 | 50.3 |
| Rarely_Never | 86 | 41.0 | 43.7 | 88.1 | 93.9 |
| Dont_know | 11 | 5.2 | 5.6 | 93.3 | 99.5 |
| Scantron_Error | 1 | 0.5 | 0.5 | 93.8 | 100.0 |
| NA | 13 | 6.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 43 | 20.5 | 22.3 | 20.5 | 22.3 |
| Sometimes | 78 | 37.1 | 40.4 | 57.6 | 62.7 |
| Rarely_Never | 60 | 28.6 | 31.1 | 86.2 | 93.8 |
| Dont_know | 12 | 5.7 | 6.2 | 91.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.9 | 100.0 |
| NA | 17 | 8.1 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 75 | 35.7 | 39.1 | 35.7 | 39.1 |
| Sometimes | 59 | 28.1 | 30.7 | 63.8 | 69.8 |
| Rarely_Never | 41 | 19.5 | 21.4 | 83.3 | 91.1 |
| Dont_know | 17 | 8.1 | 8.9 | 91.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.4 | 100.0 |
| NA | 18 | 8.6 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 51 | 16.2 | 17.7 | 16.2 | 17.7 |
| Sometimes | 109 | 34.6 | 37.8 | 50.8 | 55.6 |
| Rarely_Never | 106 | 33.7 | 36.8 | 84.4 | 92.4 |
| Dont_know | 22 | 7.0 | 7.6 | 91.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.4 | 100.0 |
| NA | 27 | 8.6 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 43 | 13.7 | 15.5 | 13.7 | 15.5 |
| Sometimes | 102 | 32.4 | 36.8 | 46.0 | 52.3 |
| Rarely_Never | 105 | 33.3 | 37.9 | 79.4 | 90.3 |
| Dont_know | 27 | 8.6 | 9.7 | 87.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 87.9 | 100.0 |
| NA | 38 | 12.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 99 | 31.4 | 35.4 | 31.4 | 35.4 |
| Sometimes | 91 | 28.9 | 32.5 | 60.3 | 67.9 |
| Rarely_Never | 63 | 20.0 | 22.5 | 80.3 | 90.4 |
| Dont_know | 27 | 8.6 | 9.6 | 88.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 88.9 | 100.0 |
| NA | 35 | 11.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 51 | 14.3 | 15.4 | 14.3 | 15.4 |
| Sometimes | 116 | 32.6 | 34.9 | 46.9 | 50.3 |
| Rarely_Never | 134 | 37.6 | 40.4 | 84.6 | 90.7 |
| Dont_know | 31 | 8.7 | 9.3 | 93.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.3 | 100.0 |
| NA | 24 | 6.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 55 | 15.4 | 17.3 | 15.4 | 17.3 |
| Sometimes | 123 | 34.6 | 38.7 | 50.0 | 56.0 |
| Rarely_Never | 110 | 30.9 | 34.6 | 80.9 | 90.6 |
| Dont_know | 30 | 8.4 | 9.4 | 89.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 89.3 | 100.0 |
| NA | 38 | 10.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 117 | 32.9 | 37.4 | 32.9 | 37.4 |
| Sometimes | 101 | 28.4 | 32.3 | 61.2 | 69.6 |
| Rarely_Never | 63 | 17.7 | 20.1 | 78.9 | 89.8 |
| Dont_know | 32 | 9.0 | 10.2 | 87.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 87.9 | 100.0 |
| NA | 43 | 12.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 118 | 20.2 | 22.0 | 20.2 | 22.0 |
| Sometimes | 180 | 30.8 | 33.5 | 50.9 | 55.5 |
| Rarely_Never | 187 | 32.0 | 34.8 | 82.9 | 90.3 |
| Dont_know | 51 | 8.7 | 9.5 | 91.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 91.8 | 100.0 |
| NA | 48 | 8.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 120 | 20.5 | 23.9 | 20.5 | 23.9 |
| Sometimes | 185 | 31.6 | 36.9 | 52.1 | 60.8 |
| Rarely_Never | 156 | 26.7 | 31.1 | 78.8 | 91.8 |
| Dont_know | 40 | 6.8 | 8.0 | 85.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 85.8 | 100.0 |
| NA | 83 | 14.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 207 | 35.4 | 41.2 | 35.4 | 41.2 |
| Sometimes | 149 | 25.5 | 29.7 | 60.9 | 70.9 |
| Rarely_Never | 94 | 16.1 | 18.7 | 76.9 | 89.6 |
| Dont_know | 50 | 8.5 | 10.0 | 85.5 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 85.8 | 100.0 |
| NA | 83 | 14.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 264 | 15.1 | 16.3 | 15.1 | 16.3 |
| Sometimes | 527 | 30.0 | 32.6 | 45.1 | 48.9 |
| Rarely_Never | 667 | 38.0 | 41.2 | 83.1 | 90.1 |
| Dont_know | 159 | 9.1 | 9.8 | 92.2 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.3 | 100.0 |
| NA | 135 | 7.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 308 | 17.6 | 19.9 | 17.6 | 19.9 |
| Sometimes | 557 | 31.8 | 35.9 | 49.3 | 55.8 |
| Rarely_Never | 543 | 31.0 | 35.0 | 80.3 | 90.8 |
| Dont_know | 143 | 8.2 | 9.2 | 88.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 88.4 | 100.0 |
| NA | 203 | 11.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 612 | 34.9 | 39.6 | 34.9 | 39.6 |
| Sometimes | 453 | 25.8 | 29.3 | 60.7 | 68.8 |
| Rarely_Never | 326 | 18.6 | 21.1 | 79.3 | 89.9 |
| Dont_know | 156 | 8.9 | 10.1 | 88.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 88.2 | 100.0 |
| NA | 207 | 11.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1 | 6.2 | 6.7 | 6.2 | 6.7 |
| Sometimes | 6 | 37.5 | 40.0 | 43.8 | 46.7 |
| Rarely_Never | 6 | 37.5 | 40.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 1 | 6.2 | 6.7 | 6.2 | 6.7 |
| Sometimes | 6 | 37.5 | 40.0 | 43.8 | 46.7 |
| Rarely_Never | 6 | 37.5 | 40.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Often | 4 | 25.0 | 26.7 | 25.0 | 26.7 |
| Sometimes | 6 | 37.5 | 40.0 | 62.5 | 66.7 |
| Rarely_Never | 3 | 18.8 | 20.0 | 81.2 | 86.7 |
| Dont_know | 2 | 12.5 | 13.3 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
# a. At any time in your life, have you ever been unfairly fired from a job or been unfairly denied a promotion?
d1aa <- as.factor(d[,"d1aa"])
levels(d1aa) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1aa <- ordered(d1aa, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1aa)
new.d <- apply_labels(new.d, d1aa = "fired or denied a promotion")
temp.d <- data.frame (new.d, d1aa)
d1ab <- as.factor(d[,"d1ab"])
levels(d1ab) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1ab <- ordered(d1ab, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1ab)
new.d <- apply_labels(new.d, d1ab = "fired or denied a promotion-stressful")
temp.d <- data.frame (new.d, d1ab)
result<-questionr::freq(temp.d$d1aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. At any time in your life, have you ever been unfairly fired from a job or been unfairly denied a promotion?
")
| n | % | val% | |
|---|---|---|---|
| No | 1779 | 50.0 | 52.0 |
| Yes | 1639 | 46.1 | 47.9 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 138 | 3.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$d1ab,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 11 | 0.3 | 100 | 0.3 | 100 |
| NA | 3546 | 99.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# b. For unfair reasons, have you ever not been hired for a job?
d1ba <- as.factor(d[,"d1ba"])
levels(d1ba) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1ba <- ordered(d1ba, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1ba)
new.d <- apply_labels(new.d, d1ba = "not be hired")
temp.d <- data.frame (new.d, d1ba)
d1bb <- as.factor(d[,"d1bb"])
levels(d1bb) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1bb <- ordered(d1bb, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1bb)
new.d <- apply_labels(new.d, d1bb = "not be hired-stressful")
temp.d <- data.frame (new.d, d1bb)
result<-questionr::freq(temp.d$d1ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. For unfair reasons, have you ever not been hired for a job?")
| n | % | val% | |
|---|---|---|---|
| No | 2072 | 58.3 | 61.6 |
| Yes | 1289 | 36.2 | 38.3 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 195 | 5.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$d1bb,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 9 | 0.3 | 100 | 0.3 | 100 |
| NA | 3548 | 99.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# c. Have you ever been unfairly stopped, searched, questioned, physically threatened or abused by the police?
d1ca <- as.factor(d[,"d1ca"])
levels(d1ca) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1ca <- ordered(d1ca, c( "No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1ca)
new.d <- apply_labels(new.d, d1ca = "By police")
temp.d <- data.frame (new.d, d1ca)
result<-questionr::freq(temp.d$d1ca,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. Have you ever been unfairly stopped, searched, questioned, physically threatened or abused by the police?")
| n | % | val% | |
|---|---|---|---|
| No | 1682 | 47.3 | 49.4 |
| Yes | 1721 | 48.4 | 50.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 154 | 4.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
d1cb <- as.factor(d[,"d1cb"])
levels(d1cb) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1cb <- ordered(d1cb, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1cb)
new.d <- apply_labels(new.d, d1cb = "By police-stressful")
temp.d <- data.frame (new.d, d1cb)
result<-questionr::freq(temp.d$d1cb,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "c. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 11 | 0.3 | 100 | 0.3 | 100 |
| NA | 3546 | 99.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# d. Have you ever been unfairly discouraged by a teacher or advisor from continuing your education?
d1da <- as.factor(d[,"d1da"])
levels(d1da) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1da <- ordered(d1da, c( "No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1da)
new.d <- apply_labels(new.d, d1da = "unfair education")
temp.d <- data.frame (new.d, d1da)
result<-questionr::freq(temp.d$d1da,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. Have you ever been unfairly discouraged by a teacher or advisor from continuing your education?")
| n | % | val% | |
|---|---|---|---|
| No | 2714 | 76.3 | 79.8 |
| Yes | 689 | 19.4 | 20.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 154 | 4.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
d1db <- as.factor(d[,"d1db"])
levels(d1db) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1db <- ordered(d1db, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1db)
new.d <- apply_labels(new.d, d1db = "unfair education-stressful")
temp.d <- data.frame (new.d, d1db)
result<-questionr::freq(temp.d$d1db,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "d. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 7 | 0.2 | 100 | 0.2 | 100 |
| NA | 3550 | 99.8 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# e. Have you ever been unfairly prevented from moving into a neighborhood because the landlord or a realtor refused to sell or rent you a house or apartment?
d1ea <- as.factor(d[,"d1ea"])
levels(d1ea) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1ea <- ordered(d1ea, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1ea)
new.d <- apply_labels(new.d, d1ea = "refuse to sell or rent")
temp.d <- data.frame (new.d, d1ea)
result<-questionr::freq(temp.d$d1ea,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. Have you ever been unfairly prevented from moving into a neighborhood because the landlord or a realtor refused to sell or rent you a house or apartment?")
| n | % | val% | |
|---|---|---|---|
| No | 2863 | 80.5 | 83.6 |
| Yes | 561 | 15.8 | 16.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 133 | 3.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
d1eb <- as.factor(d[,"d1eb"])
levels(d1eb) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1eb <- ordered(d1eb, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1eb)
new.d <- apply_labels(new.d, d1eb = "refuse to sell or rent-stressful")
temp.d <- data.frame (new.d, d1eb)
result<-questionr::freq(temp.d$d1eb,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "e. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 6 | 0.2 | 100 | 0.2 | 100 |
| NA | 3551 | 99.8 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# f. Have you ever been unfairly denied a bank loan?
d1fa <- as.factor(d[,"d1fa"])
levels(d1fa) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1fa <- ordered(d1fa, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1fa)
new.d <- apply_labels(new.d, d1fa = "Bank loan")
temp.d <- data.frame (new.d, d1fa)
result<-questionr::freq(temp.d$d1fa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. Have you ever been unfairly denied a bank loan?")
| n | % | val% | |
|---|---|---|---|
| No | 2439 | 68.6 | 71.9 |
| Yes | 953 | 26.8 | 28.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 165 | 4.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
d1fb <- as.factor(d[,"d1fb"])
levels(d1fb) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1fb <- ordered(d1fb, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1fb)
new.d <- apply_labels(new.d, d1fb = "Bank loan-stressful")
temp.d <- data.frame (new.d, d1fb)
result<-questionr::freq(temp.d$d1fb,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "f. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 7 | 0.2 | 100 | 0.2 | 100 |
| NA | 3550 | 99.8 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
# g. Have you ever been unfairly treated when getting medical care?
d1ga <- as.factor(d[,"d1ga"])
levels(d1ga) <- list(No="1",
Yes="2",
Scantron_Error="*")
d1ga <- ordered(d1ga, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1ga)
new.d <- apply_labels(new.d, d1ga = "unfair medical care")
temp.d <- data.frame (new.d, d1ga)
result<-questionr::freq(temp.d$d1ga,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g. Have you ever been unfairly treated when getting medical care?")
| n | % | val% | |
|---|---|---|---|
| No | 2856 | 80.3 | 84 |
| Yes | 543 | 15.3 | 16 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 158 | 4.4 | NA |
| Total | 3557 | 100.0 | 100 |
d1gb <- as.factor(d[,"d1gb"])
levels(d1gb) <- list(Not_at_all="1",
A_little="2",
Somewhat="3",
Extremely="4",
Scantron_Error="*")
d1gb <- ordered(d1gb, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, d1gb)
new.d <- apply_labels(new.d, d1gb = "unfair medical care-stressful")
temp.d <- data.frame (new.d, d1gb)
result<-questionr::freq(temp.d$d1gb,total = TRUE,cum=TRUE)
kable(result, format = "simple", align = 'l', caption = "g. If yes, How stressful was this experience?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 4 | 0.1 | 100 | 0.1 | 100 |
| NA | 3553 | 99.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 158 | 49.2 | 50.3 |
| Yes | 156 | 48.6 | 49.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 177 | 55.1 | 56.7 |
| Yes | 135 | 42.1 | 43.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 70 | 21.8 | 22.2 |
| Yes | 245 | 76.3 | 77.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 222 | 69.2 | 71.8 |
| Yes | 87 | 27.1 | 28.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.7 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 233 | 72.6 | 74.2 |
| Yes | 81 | 25.2 | 25.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 228 | 71.0 | 73.3 |
| Yes | 83 | 25.9 | 26.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 256 | 79.8 | 81.8 |
| Yes | 57 | 17.8 | 18.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 321 | 100 | NA | 100 | NA |
| Total | 321 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 100 | 47.6 | 49.3 |
| Yes | 103 | 49.0 | 50.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 3.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 120 | 57.1 | 58.8 |
| Yes | 84 | 40.0 | 41.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 0.5 | 100 | 0.5 | 100 |
| NA | 209 | 99.5 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 79 | 37.6 | 38.5 |
| Yes | 126 | 60.0 | 61.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | 0 | 0 | 0 |
| Yes | 0 | 0 | 0 | 0 | 0 |
| Scantron_Error | 2 | 1 | 100 | 1 | 100 |
| NA | 208 | 99 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 146 | 69.5 | 72.3 |
| Yes | 56 | 26.7 | 27.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 3.8 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 148 | 70.5 | 74.4 |
| Yes | 51 | 24.3 | 25.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 5.2 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 150 | 71.4 | 75.4 |
| Yes | 49 | 23.3 | 24.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 5.2 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 152 | 72.4 | 75.6 |
| Yes | 49 | 23.3 | 24.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 4.3 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 210 | 100 | NA | 100 | NA |
| Total | 210 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 134 | 42.5 | 44.4 |
| Yes | 168 | 53.3 | 55.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 145 | 46.0 | 49 |
| Yes | 151 | 47.9 | 51 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 19 | 6.0 | NA |
| Total | 315 | 100.0 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 113 | 35.9 | 37.5 |
| Yes | 188 | 59.7 | 62.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 224 | 71.1 | 74.4 |
| Yes | 77 | 24.4 | 25.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 2 | 0.6 | 100 | 0.6 | 100 |
| NA | 313 | 99.4 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 219 | 69.5 | 72.5 |
| Yes | 83 | 26.3 | 27.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 0.3 | 100 | 0.3 | 100 |
| NA | 314 | 99.7 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 214 | 67.9 | 71.3 |
| Yes | 86 | 27.3 | 28.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 247 | 78.4 | 81.2 |
| Yes | 57 | 18.1 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 315 | 100 | NA | 100 | NA |
| Total | 315 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 192 | 53.9 | 56.3 |
| Yes | 148 | 41.6 | 43.4 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 15 | 4.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 0.3 | 100 | 0.3 | 100 |
| NA | 355 | 99.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 212 | 59.6 | 64.4 |
| Yes | 116 | 32.6 | 35.3 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 27 | 7.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 138 | 38.8 | 41.2 |
| Yes | 197 | 55.3 | 58.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 5.9 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 249 | 69.9 | 73.9 |
| Yes | 88 | 24.7 | 26.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 19 | 5.3 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 275 | 77.2 | 80.9 |
| Yes | 65 | 18.3 | 19.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 4.5 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 248 | 69.7 | 74.3 |
| Yes | 86 | 24.2 | 25.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 22 | 6.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 282 | 79.2 | 84.4 |
| Yes | 52 | 14.6 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 22 | 6.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 356 | 100 | NA | 100 | NA |
| Total | 356 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 317 | 54.2 | 57.1 |
| Yes | 238 | 40.7 | 42.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 30 | 5.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 2 | 0.3 | 100 | 0.3 | 100 |
| NA | 583 | 99.7 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 364 | 62.2 | 66.3 |
| Yes | 185 | 31.6 | 33.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 6.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 0.2 | 100 | 0.2 | 100 |
| NA | 584 | 99.8 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 298 | 50.9 | 53.6 |
| Yes | 258 | 44.1 | 46.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 29 | 5.0 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 3 | 0.5 | 100 | 0.5 | 100 |
| NA | 582 | 99.5 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 466 | 79.7 | 83.2 |
| Yes | 94 | 16.1 | 16.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 503 | 86.0 | 89.5 |
| Yes | 59 | 10.1 | 10.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 23 | 3.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 383 | 65.5 | 68.8 |
| Yes | 174 | 29.7 | 31.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 4.8 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 0.2 | 100 | 0.2 | 100 |
| NA | 584 | 99.8 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 468 | 80.0 | 84 |
| Yes | 89 | 15.2 | 16 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 28 | 4.8 | NA |
| Total | 585 | 100.0 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0 | NaN | 0 | NaN |
| Yes | 0 | 0 | NaN | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN | 0 | NaN |
| NA | 585 | 100 | NA | 100 | NA |
| Total | 585 | 100 | 100 | 100 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 870 | 49.6 | 51.5 |
| Yes | 819 | 46.7 | 48.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 65 | 3.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 7 | 0.4 | 100 | 0.4 | 100 |
| NA | 1747 | 99.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1047 | 59.7 | 63.2 |
| Yes | 609 | 34.7 | 36.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 98 | 5.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 6 | 0.3 | 100 | 0.3 | 100 |
| NA | 1748 | 99.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 976 | 55.6 | 58.3 |
| Yes | 699 | 39.9 | 41.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 79 | 4.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 5 | 0.3 | 100 | 0.3 | 100 |
| NA | 1749 | 99.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1399 | 79.8 | 83.4 |
| Yes | 279 | 15.9 | 16.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 76 | 4.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 4 | 0.2 | 100 | 0.2 | 100 |
| NA | 1750 | 99.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1471 | 83.9 | 87 |
| Yes | 220 | 12.5 | 13 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 63 | 3.6 | NA |
| Total | 1754 | 100.0 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 4 | 0.2 | 100 | 0.2 | 100 |
| NA | 1750 | 99.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1203 | 68.6 | 71.8 |
| Yes | 472 | 26.9 | 28.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 79 | 4.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 5 | 0.3 | 100 | 0.3 | 100 |
| NA | 1749 | 99.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 1437 | 81.9 | 85.8 |
| Yes | 237 | 13.5 | 14.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 80 | 4.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 3 | 0.2 | 100 | 0.2 | 100 |
| NA | 1751 | 99.8 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 8 | 50.0 | 53.3 |
| Yes | 7 | 43.8 | 46.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 7 | 43.8 | 43.8 |
| Yes | 9 | 56.2 | 56.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 8 | 50 | 50 |
| Yes | 8 | 50 | 50 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 8 | 50 | 50 |
| Yes | 8 | 50 | 50 |
| Scantron_Error | 0 | 0 | 0 |
| Total | 16 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 81.2 |
| Yes | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 0 | 0.0 | 0 | 0.0 | 0 |
| Yes | 0 | 0.0 | 0 | 0.0 | 0 |
| Scantron_Error | 1 | 6.2 | 100 | 6.2 | 100 |
| NA | 15 | 93.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
# a. Patients have sometimes been deceived or misled at hospitals.
d2a <- as.factor(d[,"d2a"])
levels(d2a) <- list(Strongly_Agree="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d2a <- ordered(d2a, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d2a)
new.d <- apply_labels(new.d, d2a = "deceived or misled")
temp.d <- data.frame (new.d, d2a)
result<-questionr::freq(temp.d$d2a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Patients have sometimes been deceived or misled at hospitals.")
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 495 | 13.9 | 14.6 |
| Somewhat_Agree | 1436 | 40.4 | 42.4 |
| Somewhat_Disagree | 820 | 23.1 | 24.2 |
| Strongly_Disagree | 629 | 17.7 | 18.6 |
| Scantron_Error | 8 | 0.2 | 0.2 |
| NA | 169 | 4.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
# b. Hospitals often want to know more about your personal affairs or business than they really need to know.
d2b <- as.factor(d[,"d2b"])
levels(d2b) <- list(Strongly_Agree="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d2b <- ordered(d2b, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d2b)
new.d <- apply_labels(new.d, d2b = "personal affairs")
temp.d <- data.frame (new.d, d2b)
result<-questionr::freq(temp.d$d2b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Hospitals often want to know more about your personal affairs or business than they really need to know.")
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 429 | 12.1 | 12.6 |
| Somewhat_Agree | 1222 | 34.4 | 36.0 |
| Somewhat_Disagree | 1002 | 28.2 | 29.5 |
| Strongly_Disagree | 740 | 20.8 | 21.8 |
| Scantron_Error | 6 | 0.2 | 0.2 |
| NA | 158 | 4.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
# c. Hospitals have sometimes done harmful experiments on patients without their knowledge.
d2c <- as.factor(d[,"d2c"])
levels(d2c) <- list(Strongly_Agree="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d2c <- ordered(d2c, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d2c)
new.d <- apply_labels(new.d, d2c = "harmful experiments")
temp.d <- data.frame (new.d, d2c)
result<-questionr::freq(temp.d$d2c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. Hospitals have sometimes done harmful experiments on patients without their knowledge.")
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 650 | 18.3 | 19.7 |
| Somewhat_Agree | 1104 | 31.0 | 33.5 |
| Somewhat_Disagree | 824 | 23.2 | 25.0 |
| Strongly_Disagree | 707 | 19.9 | 21.5 |
| Scantron_Error | 8 | 0.2 | 0.2 |
| NA | 264 | 7.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
# d. Rich patients receive better care at hospitals than poor patients.
d2d <- as.factor(d[,"d2d"])
levels(d2d) <- list(Strongly_Agree="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d2d <- ordered(d2d, c( "Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d2d)
new.d <- apply_labels(new.d, d2d = "Rich patients better care")
temp.d <- data.frame (new.d, d2d)
result<-questionr::freq(temp.d$d2d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. Rich patients receive better care at hospitals than poor patients.")
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 1841 | 51.8 | 54.7 |
| Somewhat_Agree | 900 | 25.3 | 26.7 |
| Somewhat_Disagree | 332 | 9.3 | 9.9 |
| Strongly_Disagree | 289 | 8.1 | 8.6 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 192 | 5.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
# e. Male patients receive better care at hospitals than female patients.
d2e <- as.factor(d[,"d2e"])
levels(d2e) <- list(Strongly_Agree="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d2e <- ordered(d2e, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d2e)
new.d <- apply_labels(new.d, d2e = "Male patients better care")
temp.d <- data.frame (new.d, d2e)
result<-questionr::freq(temp.d$d2e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. Male patients receive better care at hospitals than female patients.")
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 149 | 4.2 | 4.5 |
| Somewhat_Agree | 498 | 14.0 | 15.1 |
| Somewhat_Disagree | 1447 | 40.7 | 44.0 |
| Strongly_Disagree | 1195 | 33.6 | 36.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 268 | 7.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 49 | 15.3 | 15.7 |
| Somewhat_Agree | 139 | 43.3 | 44.6 |
| Somewhat_Disagree | 79 | 24.6 | 25.3 |
| Strongly_Disagree | 45 | 14.0 | 14.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 34 | 10.6 | 10.8 |
| Somewhat_Agree | 120 | 37.4 | 38.2 |
| Somewhat_Disagree | 100 | 31.2 | 31.8 |
| Strongly_Disagree | 60 | 18.7 | 19.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 81 | 25.2 | 26.2 |
| Somewhat_Agree | 101 | 31.5 | 32.7 |
| Somewhat_Disagree | 81 | 25.2 | 26.2 |
| Strongly_Disagree | 46 | 14.3 | 14.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.7 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 179 | 55.8 | 57.0 |
| Somewhat_Agree | 95 | 29.6 | 30.3 |
| Somewhat_Disagree | 27 | 8.4 | 8.6 |
| Strongly_Disagree | 13 | 4.0 | 4.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 13 | 4.0 | 4.2 |
| Somewhat_Agree | 45 | 14.0 | 14.6 |
| Somewhat_Disagree | 154 | 48.0 | 50.0 |
| Strongly_Disagree | 96 | 29.9 | 31.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.0 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 32 | 15.2 | 16 |
| Somewhat_Agree | 80 | 38.1 | 40 |
| Somewhat_Disagree | 46 | 21.9 | 23 |
| Strongly_Disagree | 42 | 20.0 | 21 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 10 | 4.8 | NA |
| Total | 210 | 100.0 | 100 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 18 | 8.6 | 8.9 |
| Somewhat_Agree | 63 | 30.0 | 31.2 |
| Somewhat_Disagree | 61 | 29.0 | 30.2 |
| Strongly_Disagree | 60 | 28.6 | 29.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 3.8 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 46 | 21.9 | 23.4 |
| Somewhat_Agree | 58 | 27.6 | 29.4 |
| Somewhat_Disagree | 38 | 18.1 | 19.3 |
| Strongly_Disagree | 55 | 26.2 | 27.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 6.2 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 112 | 53.3 | 56.6 |
| Somewhat_Agree | 60 | 28.6 | 30.3 |
| Somewhat_Disagree | 13 | 6.2 | 6.6 |
| Strongly_Disagree | 13 | 6.2 | 6.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 5.7 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 15 | 7.1 | 7.7 |
| Somewhat_Agree | 25 | 11.9 | 12.8 |
| Somewhat_Disagree | 84 | 40.0 | 43.1 |
| Strongly_Disagree | 71 | 33.8 | 36.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 51 | 16.2 | 17.1 |
| Somewhat_Agree | 116 | 36.8 | 38.8 |
| Somewhat_Disagree | 71 | 22.5 | 23.7 |
| Strongly_Disagree | 61 | 19.4 | 20.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 27 | 8.6 | 9.0 |
| Somewhat_Agree | 85 | 27.0 | 28.3 |
| Somewhat_Disagree | 112 | 35.6 | 37.3 |
| Strongly_Disagree | 76 | 24.1 | 25.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 50 | 15.9 | 17.5 |
| Somewhat_Agree | 92 | 29.2 | 32.2 |
| Somewhat_Disagree | 71 | 22.5 | 24.8 |
| Strongly_Disagree | 73 | 23.2 | 25.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 29 | 9.2 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 165 | 52.4 | 55.9 |
| Somewhat_Agree | 78 | 24.8 | 26.4 |
| Somewhat_Disagree | 30 | 9.5 | 10.2 |
| Strongly_Disagree | 21 | 6.7 | 7.1 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 20 | 6.3 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 18 | 5.7 | 6.2 |
| Somewhat_Agree | 51 | 16.2 | 17.6 |
| Somewhat_Disagree | 130 | 41.3 | 44.8 |
| Strongly_Disagree | 91 | 28.9 | 31.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 7.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 46 | 12.9 | 13.8 |
| Somewhat_Agree | 131 | 36.8 | 39.2 |
| Somewhat_Disagree | 86 | 24.2 | 25.7 |
| Strongly_Disagree | 71 | 19.9 | 21.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 22 | 6.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 38 | 10.7 | 11.3 |
| Somewhat_Agree | 125 | 35.1 | 37.2 |
| Somewhat_Disagree | 88 | 24.7 | 26.2 |
| Strongly_Disagree | 84 | 23.6 | 25.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 20 | 5.6 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 56 | 15.7 | 17.4 |
| Somewhat_Agree | 107 | 30.1 | 33.3 |
| Somewhat_Disagree | 80 | 22.5 | 24.9 |
| Strongly_Disagree | 77 | 21.6 | 24.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 35 | 9.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 171 | 48.0 | 51.7 |
| Somewhat_Agree | 90 | 25.3 | 27.2 |
| Somewhat_Disagree | 35 | 9.8 | 10.6 |
| Strongly_Disagree | 35 | 9.8 | 10.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 7.0 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 18 | 5.1 | 5.6 |
| Somewhat_Agree | 47 | 13.2 | 14.7 |
| Somewhat_Disagree | 129 | 36.2 | 40.3 |
| Strongly_Disagree | 126 | 35.4 | 39.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 10.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 82 | 14.0 | 14.8 |
| Somewhat_Agree | 223 | 38.1 | 40.3 |
| Somewhat_Disagree | 137 | 23.4 | 24.8 |
| Strongly_Disagree | 107 | 18.3 | 19.3 |
| Scantron_Error | 4 | 0.7 | 0.7 |
| NA | 32 | 5.5 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 78 | 13.3 | 14.2 |
| Somewhat_Agree | 199 | 34.0 | 36.1 |
| Somewhat_Disagree | 144 | 24.6 | 26.1 |
| Strongly_Disagree | 129 | 22.1 | 23.4 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 34 | 5.8 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 102 | 17.4 | 19.3 |
| Somewhat_Agree | 165 | 28.2 | 31.2 |
| Somewhat_Disagree | 133 | 22.7 | 25.1 |
| Strongly_Disagree | 129 | 22.1 | 24.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 56 | 9.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 275 | 47.0 | 49.5 |
| Somewhat_Agree | 152 | 26.0 | 27.4 |
| Somewhat_Disagree | 62 | 10.6 | 11.2 |
| Strongly_Disagree | 65 | 11.1 | 11.7 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 30 | 5.1 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 22 | 3.8 | 4.1 |
| Somewhat_Agree | 77 | 13.2 | 14.3 |
| Somewhat_Disagree | 236 | 40.3 | 43.7 |
| Strongly_Disagree | 205 | 35.0 | 38.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 45 | 7.7 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 234 | 13.3 | 14.0 |
| Somewhat_Agree | 741 | 42.2 | 44.3 |
| Somewhat_Disagree | 398 | 22.7 | 23.8 |
| Strongly_Disagree | 297 | 16.9 | 17.7 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 80 | 4.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 233 | 13.3 | 13.9 |
| Somewhat_Agree | 625 | 35.6 | 37.2 |
| Somewhat_Disagree | 492 | 28.1 | 29.3 |
| Strongly_Disagree | 326 | 18.6 | 19.4 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 74 | 4.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 313 | 17.8 | 19.1 |
| Somewhat_Agree | 578 | 33.0 | 35.4 |
| Somewhat_Disagree | 417 | 23.8 | 25.5 |
| Strongly_Disagree | 321 | 18.3 | 19.6 |
| Scantron_Error | 6 | 0.3 | 0.4 |
| NA | 119 | 6.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 933 | 53.2 | 56.3 |
| Somewhat_Agree | 419 | 23.9 | 25.3 |
| Somewhat_Disagree | 163 | 9.3 | 9.8 |
| Strongly_Disagree | 140 | 8.0 | 8.5 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 98 | 5.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 62 | 3.5 | 3.8 |
| Somewhat_Agree | 251 | 14.3 | 15.5 |
| Somewhat_Disagree | 708 | 40.4 | 43.7 |
| Strongly_Disagree | 599 | 34.2 | 37.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 134 | 7.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 1 | 6.2 | 6.2 |
| Somewhat_Agree | 6 | 37.5 | 37.5 |
| Somewhat_Disagree | 3 | 18.8 | 18.8 |
| Strongly_Disagree | 6 | 37.5 | 37.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 1 | 6.2 | 6.2 |
| Somewhat_Agree | 5 | 31.2 | 31.2 |
| Somewhat_Disagree | 5 | 31.2 | 31.2 |
| Strongly_Disagree | 5 | 31.2 | 31.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 2 | 12.5 | 12.5 |
| Somewhat_Agree | 3 | 18.8 | 18.8 |
| Somewhat_Disagree | 4 | 25.0 | 25.0 |
| Strongly_Disagree | 6 | 37.5 | 37.5 |
| Scantron_Error | 1 | 6.2 | 6.2 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 6 | 37.5 | 37.5 |
| Somewhat_Agree | 6 | 37.5 | 37.5 |
| Somewhat_Disagree | 2 | 12.5 | 12.5 |
| Strongly_Disagree | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Strongly_Agree | 1 | 6.2 | 6.2 |
| Somewhat_Agree | 2 | 12.5 | 12.5 |
| Somewhat_Disagree | 6 | 37.5 | 37.5 |
| Strongly_Disagree | 7 | 43.8 | 43.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
# 1
d3a1 <- as.factor(d[,"d3a1"])
levels(d3a1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3a1 <- ordered(d3a1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3a1)
new.d <- apply_labels(new.d, d3a1 = "less respect-current")
temp.d <- data.frame (new.d, d3a1)
result<-questionr::freq(temp.d$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1048 | 29.5 | 30.2 |
| Rarely | 1014 | 28.5 | 29.2 |
| Sometimes | 1207 | 33.9 | 34.8 |
| Often | 198 | 5.6 | 5.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 88 | 2.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3a2 <- as.factor(d[,"d3a2"])
levels(d3a2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3a2 <- ordered(d3a2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3a2)
new.d <- apply_labels(new.d, d3a2 = "less respect-31 up")
temp.d <- data.frame (new.d, d3a2)
result<-questionr::freq(temp.d$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 782 | 22.0 | 23.8 |
| Rarely | 957 | 26.9 | 29.1 |
| Sometimes | 1275 | 35.8 | 38.8 |
| Often | 269 | 7.6 | 8.2 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 272 | 7.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3a3 <- as.factor(d[,"d3a3"])
levels(d3a3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3a3 <- ordered(d3a3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3a3)
new.d <- apply_labels(new.d, d3a3 = "less respect-child or young")
temp.d <- data.frame (new.d, d3a3)
result<-questionr::freq(temp.d$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 719 | 20.2 | 22.1 |
| Rarely | 717 | 20.2 | 22.0 |
| Sometimes | 1238 | 34.8 | 38.0 |
| Often | 576 | 16.2 | 17.7 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 303 | 8.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 84 | 26.2 | 26.4 |
| Rarely | 100 | 31.2 | 31.4 |
| Sometimes | 116 | 36.1 | 36.5 |
| Often | 18 | 5.6 | 5.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 57 | 17.8 | 18.2 |
| Rarely | 89 | 27.7 | 28.4 |
| Sometimes | 146 | 45.5 | 46.6 |
| Often | 21 | 6.5 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 54 | 16.8 | 17.3 |
| Rarely | 72 | 22.4 | 23.0 |
| Sometimes | 142 | 44.2 | 45.4 |
| Often | 45 | 14.0 | 14.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 52 | 24.8 | 25.5 |
| Rarely | 56 | 26.7 | 27.5 |
| Sometimes | 75 | 35.7 | 36.8 |
| Often | 21 | 10.0 | 10.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 40 | 19.0 | 20.4 |
| Rarely | 59 | 28.1 | 30.1 |
| Sometimes | 74 | 35.2 | 37.8 |
| Often | 23 | 11.0 | 11.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 41 | 19.5 | 21.1 |
| Rarely | 45 | 21.4 | 23.2 |
| Sometimes | 66 | 31.4 | 34.0 |
| Often | 42 | 20.0 | 21.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 7.6 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 65 | 20.6 | 21.5 |
| Rarely | 89 | 28.3 | 29.5 |
| Sometimes | 122 | 38.7 | 40.4 |
| Often | 26 | 8.3 | 8.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 45 | 14.3 | 15.5 |
| Rarely | 79 | 25.1 | 27.2 |
| Sometimes | 129 | 41.0 | 44.5 |
| Often | 37 | 11.7 | 12.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 7.9 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 48 | 15.2 | 16.5 |
| Rarely | 59 | 18.7 | 20.3 |
| Sometimes | 116 | 36.8 | 39.9 |
| Often | 67 | 21.3 | 23.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 111 | 31.2 | 31.6 |
| Rarely | 122 | 34.3 | 34.8 |
| Sometimes | 103 | 28.9 | 29.3 |
| Often | 15 | 4.2 | 4.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.4 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 81 | 22.8 | 25.2 |
| Rarely | 117 | 32.9 | 36.3 |
| Sometimes | 104 | 29.2 | 32.3 |
| Often | 20 | 5.6 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 34 | 9.6 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 78 | 21.9 | 24.5 |
| Rarely | 87 | 24.4 | 27.3 |
| Sometimes | 117 | 32.9 | 36.7 |
| Often | 37 | 10.4 | 11.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 37 | 10.4 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 185 | 31.6 | 32.3 |
| Rarely | 141 | 24.1 | 24.7 |
| Sometimes | 206 | 35.2 | 36.0 |
| Often | 39 | 6.7 | 6.8 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 13 | 2.2 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 144 | 24.6 | 27.5 |
| Rarely | 132 | 22.6 | 25.2 |
| Sometimes | 195 | 33.3 | 37.2 |
| Often | 52 | 8.9 | 9.9 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 61 | 10.4 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 131 | 22.4 | 25.1 |
| Rarely | 95 | 16.2 | 18.2 |
| Sometimes | 202 | 34.5 | 38.7 |
| Often | 93 | 15.9 | 17.8 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 63 | 10.8 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 545 | 31.1 | 31.9 |
| Rarely | 501 | 28.6 | 29.4 |
| Sometimes | 580 | 33.1 | 34.0 |
| Often | 79 | 4.5 | 4.6 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 48 | 2.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 410 | 23.4 | 25.2 |
| Rarely | 478 | 27.3 | 29.4 |
| Sometimes | 620 | 35.3 | 38.2 |
| Often | 116 | 6.6 | 7.1 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 129 | 7.4 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 366 | 20.9 | 22.9 |
| Rarely | 351 | 20.0 | 21.9 |
| Sometimes | 591 | 33.7 | 36.9 |
| Often | 291 | 16.6 | 18.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 154 | 8.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3a1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 6 | 37.5 | 37.5 |
| Rarely | 5 | 31.2 | 31.2 |
| Sometimes | 5 | 31.2 | 31.2 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 33.3 |
| Rarely | 3 | 18.8 | 20.0 |
| Sometimes | 7 | 43.8 | 46.7 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3a3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 1 | 6.2 | 6.7 |
| Rarely | 8 | 50.0 | 53.3 |
| Sometimes | 4 | 25.0 | 26.7 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 1 | 6.2 | 6.7 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3b1 <- as.factor(d[,"d3b1"])
levels(d3b1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3b1 <- ordered(d3b1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3b1)
new.d <- apply_labels(new.d, d3b1 = "poorer service-current")
temp.d <- data.frame (new.d, d3b1)
result<-questionr::freq(temp.d$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 795 | 22.4 | 23.1 |
| Rarely | 1124 | 31.6 | 32.7 |
| Sometimes | 1344 | 37.8 | 39.0 |
| Often | 178 | 5.0 | 5.2 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 115 | 3.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3b2 <- as.factor(d[,"d3b2"])
levels(d3b2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3b2 <- ordered(d3b2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3b2)
new.d <- apply_labels(new.d, d3b2 = "poorer service-31 up")
temp.d <- data.frame (new.d, d3b2)
result<-questionr::freq(temp.d$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 601 | 16.9 | 18.4 |
| Rarely | 978 | 27.5 | 30.0 |
| Sometimes | 1451 | 40.8 | 44.5 |
| Often | 229 | 6.4 | 7.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 298 | 8.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3b3 <- as.factor(d[,"d3b3"])
levels(d3b3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3b3 <- ordered(d3b3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3b3)
new.d <- apply_labels(new.d, d3b3 = "poorer service-child or young")
temp.d <- data.frame (new.d, d3b3)
result<-questionr::freq(temp.d$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 603 | 17.0 | 18.7 |
| Rarely | 728 | 20.5 | 22.6 |
| Sometimes | 1332 | 37.4 | 41.4 |
| Often | 556 | 15.6 | 17.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 338 | 9.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 64 | 19.9 | 20.2 |
| Rarely | 116 | 36.1 | 36.6 |
| Sometimes | 119 | 37.1 | 37.5 |
| Often | 18 | 5.6 | 5.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 46 | 14.3 | 14.8 |
| Rarely | 102 | 31.8 | 32.8 |
| Sometimes | 144 | 44.9 | 46.3 |
| Often | 19 | 5.9 | 6.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 40 | 12.5 | 12.9 |
| Rarely | 95 | 29.6 | 30.6 |
| Sometimes | 142 | 44.2 | 45.8 |
| Often | 33 | 10.3 | 10.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.4 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 35 | 16.7 | 17.2 |
| Rarely | 66 | 31.4 | 32.4 |
| Sometimes | 84 | 40.0 | 41.2 |
| Often | 19 | 9.0 | 9.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 29 | 13.8 | 14.9 |
| Rarely | 58 | 27.6 | 29.9 |
| Sometimes | 84 | 40.0 | 43.3 |
| Often | 23 | 11.0 | 11.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 7.6 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 32 | 15.2 | 16.8 |
| Rarely | 43 | 20.5 | 22.5 |
| Sometimes | 85 | 40.5 | 44.5 |
| Often | 31 | 14.8 | 16.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 19 | 9.0 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 66 | 21.0 | 22.0 |
| Rarely | 94 | 29.8 | 31.3 |
| Sometimes | 121 | 38.4 | 40.3 |
| Often | 18 | 5.7 | 6.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 15 | 4.8 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 48 | 15.2 | 16.5 |
| Rarely | 85 | 27.0 | 29.2 |
| Sometimes | 135 | 42.9 | 46.4 |
| Often | 23 | 7.3 | 7.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 51 | 16.2 | 17.7 |
| Rarely | 56 | 17.8 | 19.4 |
| Sometimes | 122 | 38.7 | 42.4 |
| Often | 59 | 18.7 | 20.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 27 | 8.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 88 | 24.7 | 25.1 |
| Rarely | 123 | 34.6 | 35.1 |
| Sometimes | 119 | 33.4 | 34.0 |
| Often | 20 | 5.6 | 5.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.7 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 63 | 17.7 | 19.6 |
| Rarely | 112 | 31.5 | 34.8 |
| Sometimes | 126 | 35.4 | 39.1 |
| Often | 21 | 5.9 | 6.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 34 | 9.6 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 63 | 17.7 | 19.9 |
| Rarely | 85 | 23.9 | 26.9 |
| Sometimes | 133 | 37.4 | 42.1 |
| Often | 35 | 9.8 | 11.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 40 | 11.2 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 160 | 27.4 | 28.6 |
| Rarely | 153 | 26.2 | 27.4 |
| Sometimes | 216 | 36.9 | 38.6 |
| Often | 30 | 5.1 | 5.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 26 | 4.4 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 111 | 19.0 | 21.7 |
| Rarely | 131 | 22.4 | 25.6 |
| Sometimes | 225 | 38.5 | 44.0 |
| Often | 44 | 7.5 | 8.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 74 | 12.6 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 105 | 17.9 | 20.5 |
| Rarely | 91 | 15.6 | 17.8 |
| Sometimes | 212 | 36.2 | 41.4 |
| Often | 104 | 17.8 | 20.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 73 | 12.5 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 376 | 21.4 | 22.2 |
| Rarely | 568 | 32.4 | 33.5 |
| Sometimes | 681 | 38.8 | 40.2 |
| Often | 71 | 4.0 | 4.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 58 | 3.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 298 | 17.0 | 18.5 |
| Rarely | 486 | 27.7 | 30.1 |
| Sometimes | 734 | 41.8 | 45.4 |
| Often | 97 | 5.5 | 6.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 139 | 7.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 308 | 17.6 | 19.4 |
| Rarely | 354 | 20.2 | 22.3 |
| Sometimes | 634 | 36.1 | 39.9 |
| Often | 291 | 16.6 | 18.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 167 | 9.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3b1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 6 | 37.5 | 37.5 |
| Rarely | 4 | 25.0 | 25.0 |
| Sometimes | 4 | 25.0 | 25.0 |
| Often | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 6 | 37.5 | 40.0 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 3 | 18.8 | 20.0 |
| Often | 2 | 12.5 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3b3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 4 | 25.0 | 26.7 |
| Often | 3 | 18.8 | 20.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3c1 <- as.factor(d[,"d3c1"])
levels(d3c1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3c1 <- ordered(d3c1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3c1)
new.d <- apply_labels(new.d, d3c1 = "think you are not smart-current")
temp.d <- data.frame (new.d, d3c1)
result<-questionr::freq(temp.d$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 968 | 27.2 | 28.3 |
| Rarely | 1055 | 29.7 | 30.9 |
| Sometimes | 1118 | 31.4 | 32.7 |
| Often | 276 | 7.8 | 8.1 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 139 | 3.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3c2 <- as.factor(d[,"d3c2"])
levels(d3c2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3c2 <- ordered(d3c2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3c2)
new.d <- apply_labels(new.d, d3c2 = "think you are not smart-31 up")
temp.d <- data.frame (new.d, d3c2)
result<-questionr::freq(temp.d$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 788 | 22.2 | 24.3 |
| Rarely | 1016 | 28.6 | 31.3 |
| Sometimes | 1154 | 32.4 | 35.6 |
| Often | 286 | 8.0 | 8.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 313 | 8.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3c3 <- as.factor(d[,"d3c3"])
levels(d3c3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3c3 <- ordered(d3c3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3c3)
new.d <- apply_labels(new.d, d3c3 = "think you are not smart-child or young")
temp.d <- data.frame (new.d, d3c3)
result<-questionr::freq(temp.d$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 725 | 20.4 | 22.5 |
| Rarely | 812 | 22.8 | 25.2 |
| Sometimes | 1194 | 33.6 | 37.1 |
| Often | 486 | 13.7 | 15.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 340 | 9.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 72 | 22.4 | 22.9 |
| Rarely | 113 | 35.2 | 36.0 |
| Sometimes | 103 | 32.1 | 32.8 |
| Often | 26 | 8.1 | 8.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 57 | 17.8 | 18.6 |
| Rarely | 97 | 30.2 | 31.6 |
| Sometimes | 128 | 39.9 | 41.7 |
| Often | 25 | 7.8 | 8.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 52 | 16.2 | 17.0 |
| Rarely | 82 | 25.5 | 26.8 |
| Sometimes | 135 | 42.1 | 44.1 |
| Often | 37 | 11.5 | 12.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.7 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 42 | 20.0 | 20.4 |
| Rarely | 72 | 34.3 | 35.0 |
| Sometimes | 70 | 33.3 | 34.0 |
| Often | 22 | 10.5 | 10.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 41 | 19.5 | 20.8 |
| Rarely | 64 | 30.5 | 32.5 |
| Sometimes | 69 | 32.9 | 35.0 |
| Often | 23 | 11.0 | 11.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 6.2 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 39 | 18.6 | 20.0 |
| Rarely | 52 | 24.8 | 26.7 |
| Sometimes | 69 | 32.9 | 35.4 |
| Often | 35 | 16.7 | 17.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 79 | 25.1 | 26.6 |
| Rarely | 88 | 27.9 | 29.6 |
| Sometimes | 105 | 33.3 | 35.4 |
| Often | 25 | 7.9 | 8.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 5.7 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 61 | 19.4 | 21.3 |
| Rarely | 76 | 24.1 | 26.5 |
| Sometimes | 120 | 38.1 | 41.8 |
| Often | 30 | 9.5 | 10.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 8.9 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 60 | 19.0 | 21.1 |
| Rarely | 63 | 20.0 | 22.1 |
| Sometimes | 106 | 33.7 | 37.2 |
| Often | 56 | 17.8 | 19.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 30 | 9.5 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 106 | 29.8 | 31.0 |
| Rarely | 106 | 29.8 | 31.0 |
| Sometimes | 108 | 30.3 | 31.6 |
| Often | 22 | 6.2 | 6.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 3.9 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 85 | 23.9 | 26.6 |
| Rarely | 103 | 28.9 | 32.2 |
| Sometimes | 104 | 29.2 | 32.5 |
| Often | 28 | 7.9 | 8.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 10.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 80 | 22.5 | 25.5 |
| Rarely | 87 | 24.4 | 27.7 |
| Sometimes | 107 | 30.1 | 34.1 |
| Often | 40 | 11.2 | 12.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 42 | 11.8 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 165 | 28.2 | 29.6 |
| Rarely | 141 | 24.1 | 25.3 |
| Sometimes | 200 | 34.2 | 35.9 |
| Often | 51 | 8.7 | 9.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 4.8 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 138 | 23.6 | 26.6 |
| Rarely | 141 | 24.1 | 27.2 |
| Sometimes | 188 | 32.1 | 36.3 |
| Often | 51 | 8.7 | 9.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 67 | 11.5 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 126 | 21.5 | 24.4 |
| Rarely | 122 | 20.9 | 23.6 |
| Sometimes | 180 | 30.8 | 34.8 |
| Often | 89 | 15.2 | 17.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 68 | 11.6 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 499 | 28.4 | 29.6 |
| Rarely | 531 | 30.3 | 31.5 |
| Sometimes | 527 | 30.0 | 31.2 |
| Often | 129 | 7.4 | 7.6 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 67 | 3.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 402 | 22.9 | 25.1 |
| Rarely | 530 | 30.2 | 33.1 |
| Sometimes | 543 | 31.0 | 33.9 |
| Often | 127 | 7.2 | 7.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 152 | 8.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 363 | 20.7 | 22.9 |
| Rarely | 403 | 23.0 | 25.4 |
| Sometimes | 594 | 33.9 | 37.4 |
| Often | 227 | 12.9 | 14.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 167 | 9.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3c1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 33.3 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 5 | 31.2 | 33.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 30.8 |
| Rarely | 5 | 31.2 | 38.5 |
| Sometimes | 2 | 12.5 | 15.4 |
| Often | 2 | 12.5 | 15.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 18.8 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3c3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 38.5 |
| Rarely | 3 | 18.8 | 23.1 |
| Sometimes | 3 | 18.8 | 23.1 |
| Often | 2 | 12.5 | 15.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 18.8 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3d1 <- as.factor(d[,"d3d1"])
levels(d3d1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3d1 <- ordered(d3d1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3d1)
new.d <- apply_labels(new.d, d3d1 = "be afraid of you-current")
temp.d <- data.frame (new.d, d3d1)
result<-questionr::freq(temp.d$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1289 | 36.2 | 37.4 |
| Rarely | 961 | 27.0 | 27.9 |
| Sometimes | 974 | 27.4 | 28.3 |
| Often | 218 | 6.1 | 6.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 115 | 3.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3d2 <- as.factor(d[,"d3d2"])
levels(d3d2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3d2 <- ordered(d3d2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3d2)
new.d <- apply_labels(new.d, d3d2 = "be afraid of you-31 up")
temp.d <- data.frame (new.d, d3d2)
result<-questionr::freq(temp.d$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 1025 | 28.8 | 31.5 |
| Rarely | 874 | 24.6 | 26.8 |
| Sometimes | 1064 | 29.9 | 32.7 |
| Often | 294 | 8.3 | 9.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 300 | 8.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3d3 <- as.factor(d[,"d3d3"])
levels(d3d3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3d3 <- ordered(d3d3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3d3)
new.d <- apply_labels(new.d, d3d3 = "be afraid of you-child or young")
temp.d <- data.frame (new.d, d3d3)
result<-questionr::freq(temp.d$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 1096 | 30.8 | 33.9 |
| Rarely | 795 | 22.4 | 24.6 |
| Sometimes | 961 | 27.0 | 29.7 |
| Often | 380 | 10.7 | 11.8 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 324 | 9.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 90 | 28.0 | 28.8 |
| Rarely | 88 | 27.4 | 28.1 |
| Sometimes | 106 | 33.0 | 33.9 |
| Often | 29 | 9.0 | 9.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 71 | 22.1 | 23.0 |
| Rarely | 74 | 23.1 | 23.9 |
| Sometimes | 130 | 40.5 | 42.1 |
| Often | 34 | 10.6 | 11.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.7 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 75 | 23.4 | 24.4 |
| Rarely | 73 | 22.7 | 23.7 |
| Sometimes | 119 | 37.1 | 38.6 |
| Often | 41 | 12.8 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.0 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 41 | 19.5 | 20.1 |
| Rarely | 63 | 30.0 | 30.9 |
| Sometimes | 77 | 36.7 | 37.7 |
| Often | 23 | 11.0 | 11.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 34 | 16.2 | 17.3 |
| Rarely | 54 | 25.7 | 27.6 |
| Sometimes | 76 | 36.2 | 38.8 |
| Often | 32 | 15.2 | 16.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 42 | 20.0 | 21.6 |
| Rarely | 51 | 24.3 | 26.3 |
| Sometimes | 69 | 32.9 | 35.6 |
| Often | 32 | 15.2 | 16.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 7.6 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 81 | 25.7 | 26.8 |
| Rarely | 93 | 29.5 | 30.8 |
| Sometimes | 101 | 32.1 | 33.4 |
| Often | 27 | 8.6 | 8.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 67 | 21.3 | 23.1 |
| Rarely | 75 | 23.8 | 25.9 |
| Sometimes | 106 | 33.7 | 36.6 |
| Often | 42 | 13.3 | 14.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 7.9 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 74 | 23.5 | 25.7 |
| Rarely | 65 | 20.6 | 22.6 |
| Sometimes | 101 | 32.1 | 35.1 |
| Often | 48 | 15.2 | 16.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 27 | 8.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 127 | 35.7 | 37.0 |
| Rarely | 101 | 28.4 | 29.4 |
| Sometimes | 93 | 26.1 | 27.1 |
| Often | 22 | 6.2 | 6.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 3.7 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 100 | 28.1 | 30.9 |
| Rarely | 88 | 24.7 | 27.2 |
| Sometimes | 107 | 30.1 | 33.0 |
| Often | 29 | 8.1 | 9.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 32 | 9.0 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 111 | 31.2 | 34.9 |
| Rarely | 84 | 23.6 | 26.4 |
| Sometimes | 86 | 24.2 | 27.0 |
| Often | 37 | 10.4 | 11.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 38 | 10.7 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 247 | 42.2 | 44.1 |
| Rarely | 135 | 23.1 | 24.1 |
| Sometimes | 155 | 26.5 | 27.7 |
| Often | 23 | 3.9 | 4.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 185 | 31.6 | 36.1 |
| Rarely | 137 | 23.4 | 26.7 |
| Sometimes | 152 | 26.0 | 29.6 |
| Often | 39 | 6.7 | 7.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 72 | 12.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 197 | 33.7 | 38.2 |
| Rarely | 118 | 20.2 | 22.9 |
| Sometimes | 147 | 25.1 | 28.5 |
| Often | 54 | 9.2 | 10.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 69 | 11.8 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 699 | 39.9 | 41.0 |
| Rarely | 478 | 27.3 | 28.1 |
| Sometimes | 436 | 24.9 | 25.6 |
| Often | 91 | 5.2 | 5.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 50 | 2.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 564 | 32.2 | 35.0 |
| Rarely | 442 | 25.2 | 27.5 |
| Sometimes | 489 | 27.9 | 30.4 |
| Often | 115 | 6.6 | 7.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 144 | 8.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 593 | 33.8 | 37.2 |
| Rarely | 400 | 22.8 | 25.1 |
| Sometimes | 436 | 24.9 | 27.4 |
| Often | 164 | 9.4 | 10.3 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 160 | 9.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3d1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 25.0 |
| Rarely | 3 | 18.8 | 18.8 |
| Sometimes | 6 | 37.5 | 37.5 |
| Often | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 4 | 25.0 | 26.7 |
| Often | 3 | 18.8 | 20.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3d3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 3 | 18.8 | 20.0 |
| Often | 4 | 25.0 | 26.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3e1 <- as.factor(d[,"d3e1"])
levels(d3e1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3e1 <- ordered(d3e1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3e1)
new.d <- apply_labels(new.d, d3e1 = "think you are dishonest-current")
temp.d <- data.frame (new.d, d3e1)
result<-questionr::freq(temp.d$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1498 | 42.1 | 43.5 |
| Rarely | 1001 | 28.1 | 29.1 |
| Sometimes | 765 | 21.5 | 22.2 |
| Often | 174 | 4.9 | 5.1 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 116 | 3.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3e2 <- as.factor(d[,"d3e2"])
levels(d3e2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3e2 <- ordered(d3e2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3e2)
new.d <- apply_labels(new.d, d3e2 = "think you are dishonest-31 up")
temp.d <- data.frame (new.d, d3e2)
result<-questionr::freq(temp.d$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 1207 | 33.9 | 37.1 |
| Rarely | 951 | 26.7 | 29.2 |
| Sometimes | 885 | 24.9 | 27.2 |
| Often | 211 | 5.9 | 6.5 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 302 | 8.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3e3 <- as.factor(d[,"d3e3"])
levels(d3e3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3e3 <- ordered(d3e3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3e3)
new.d <- apply_labels(new.d, d3e3 = "think you are dishonest-child or young")
temp.d <- data.frame (new.d, d3e3)
result<-questionr::freq(temp.d$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 1179 | 33.1 | 36.5 |
| Rarely | 793 | 22.3 | 24.5 |
| Sometimes | 904 | 25.4 | 28.0 |
| Often | 356 | 10.0 | 11.0 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 324 | 9.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 116 | 36.1 | 36.7 |
| Rarely | 103 | 32.1 | 32.6 |
| Sometimes | 78 | 24.3 | 24.7 |
| Often | 19 | 5.9 | 6.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 89 | 27.7 | 28.5 |
| Rarely | 106 | 33.0 | 34.0 |
| Sometimes | 95 | 29.6 | 30.4 |
| Often | 22 | 6.9 | 7.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 86 | 26.8 | 27.6 |
| Rarely | 85 | 26.5 | 27.2 |
| Sometimes | 111 | 34.6 | 35.6 |
| Often | 30 | 9.3 | 9.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 67 | 31.9 | 32.7 |
| Rarely | 62 | 29.5 | 30.2 |
| Sometimes | 58 | 27.6 | 28.3 |
| Often | 18 | 8.6 | 8.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 57 | 27.1 | 29.1 |
| Rarely | 54 | 25.7 | 27.6 |
| Sometimes | 65 | 31.0 | 33.2 |
| Often | 20 | 9.5 | 10.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 53 | 25.2 | 27.2 |
| Rarely | 51 | 24.3 | 26.2 |
| Sometimes | 65 | 31.0 | 33.3 |
| Often | 26 | 12.4 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 118 | 37.5 | 39.2 |
| Rarely | 94 | 29.8 | 31.2 |
| Sometimes | 74 | 23.5 | 24.6 |
| Often | 15 | 4.8 | 5.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 88 | 27.9 | 30.4 |
| Rarely | 87 | 27.6 | 30.1 |
| Sometimes | 89 | 28.3 | 30.8 |
| Often | 25 | 7.9 | 8.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 26 | 8.3 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 83 | 26.3 | 28.9 |
| Rarely | 75 | 23.8 | 26.1 |
| Sometimes | 93 | 29.5 | 32.4 |
| Often | 36 | 11.4 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 8.9 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 144 | 40.4 | 42.0 |
| Rarely | 103 | 28.9 | 30.0 |
| Sometimes | 77 | 21.6 | 22.4 |
| Often | 19 | 5.3 | 5.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 3.7 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 115 | 32.3 | 36.1 |
| Rarely | 93 | 26.1 | 29.2 |
| Sometimes | 89 | 25.0 | 27.9 |
| Often | 22 | 6.2 | 6.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 37 | 10.4 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 113 | 31.7 | 35.9 |
| Rarely | 78 | 21.9 | 24.8 |
| Sometimes | 93 | 26.1 | 29.5 |
| Often | 31 | 8.7 | 9.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 41 | 11.5 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 262 | 44.8 | 46.8 |
| Rarely | 136 | 23.2 | 24.3 |
| Sometimes | 132 | 22.6 | 23.6 |
| Often | 29 | 5.0 | 5.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 208 | 35.6 | 40.4 |
| Rarely | 131 | 22.4 | 25.4 |
| Sometimes | 145 | 24.8 | 28.2 |
| Often | 31 | 5.3 | 6.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 70 | 12.0 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 209 | 35.7 | 40.4 |
| Rarely | 106 | 18.1 | 20.5 |
| Sometimes | 139 | 23.8 | 26.9 |
| Often | 62 | 10.6 | 12.0 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 68 | 11.6 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 787 | 44.9 | 46.3 |
| Rarely | 497 | 28.3 | 29.2 |
| Sometimes | 341 | 19.4 | 20.0 |
| Often | 74 | 4.2 | 4.4 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 53 | 3.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 646 | 36.8 | 40.1 |
| Rarely | 475 | 27.1 | 29.5 |
| Sometimes | 397 | 22.6 | 24.7 |
| Often | 90 | 5.1 | 5.6 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 145 | 8.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 630 | 35.9 | 39.6 |
| Rarely | 394 | 22.5 | 24.7 |
| Sometimes | 398 | 22.7 | 25.0 |
| Often | 170 | 9.7 | 10.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 162 | 9.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3e1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 6 | 37.5 | 40.0 |
| Sometimes | 5 | 31.2 | 33.3 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 5 | 31.2 | 33.3 |
| Sometimes | 5 | 31.2 | 33.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 33.3 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 5 | 31.2 | 33.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3f1 <- as.factor(d[,"d3f1"])
levels(d3f1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3f1 <- ordered(d3f1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3f1)
new.d <- apply_labels(new.d, d3f1 = "better than you-current")
temp.d <- data.frame (new.d, d3f1)
result<-questionr::freq(temp.d$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 550 | 15.5 | 16.0 |
| Rarely | 948 | 26.7 | 27.6 |
| Sometimes | 1500 | 42.2 | 43.6 |
| Often | 441 | 12.4 | 12.8 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 117 | 3.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3f2 <- as.factor(d[,"d3f2"])
levels(d3f2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3f2 <- ordered(d3f2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3f2)
new.d <- apply_labels(new.d, d3f2 = "better than you-31 up")
temp.d <- data.frame (new.d, d3f2)
result<-questionr::freq(temp.d$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 408 | 11.5 | 12.5 |
| Rarely | 836 | 23.5 | 25.6 |
| Sometimes | 1553 | 43.7 | 47.6 |
| Often | 468 | 13.2 | 14.3 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 291 | 8.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3f3 <- as.factor(d[,"d3f3"])
levels(d3f3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3f3 <- ordered(d3f3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3f3)
new.d <- apply_labels(new.d, d3f3 = "better than you-child or young")
temp.d <- data.frame (new.d, d3f3)
result<-questionr::freq(temp.d$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 413 | 11.6 | 12.7 |
| Rarely | 664 | 18.7 | 20.5 |
| Sometimes | 1415 | 39.8 | 43.6 |
| Often | 747 | 21.0 | 23.0 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 314 | 8.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 44 | 13.7 | 14.0 |
| Rarely | 95 | 29.6 | 30.2 |
| Sometimes | 133 | 41.4 | 42.2 |
| Often | 43 | 13.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 38 | 11.8 | 12.2 |
| Rarely | 82 | 25.5 | 26.3 |
| Sometimes | 143 | 44.5 | 45.8 |
| Often | 49 | 15.3 | 15.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 42 | 13.1 | 13.5 |
| Rarely | 69 | 21.5 | 22.3 |
| Sometimes | 142 | 44.2 | 45.8 |
| Often | 57 | 17.8 | 18.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.4 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 24 | 11.4 | 11.7 |
| Rarely | 52 | 24.8 | 25.4 |
| Sometimes | 97 | 46.2 | 47.3 |
| Often | 32 | 15.2 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 23 | 11.0 | 11.7 |
| Rarely | 49 | 23.3 | 25.0 |
| Sometimes | 91 | 43.3 | 46.4 |
| Often | 33 | 15.7 | 16.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 23 | 11.0 | 11.8 |
| Rarely | 33 | 15.7 | 16.9 |
| Sometimes | 95 | 45.2 | 48.7 |
| Often | 44 | 21.0 | 22.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 44 | 14.0 | 14.7 |
| Rarely | 79 | 25.1 | 26.4 |
| Sometimes | 128 | 40.6 | 42.8 |
| Often | 48 | 15.2 | 16.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 32 | 10.2 | 11.1 |
| Rarely | 63 | 20.0 | 21.8 |
| Sometimes | 139 | 44.1 | 48.1 |
| Often | 55 | 17.5 | 19.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 26 | 8.3 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 30 | 9.5 | 10.5 |
| Rarely | 64 | 20.3 | 22.5 |
| Sometimes | 111 | 35.2 | 38.9 |
| Often | 80 | 25.4 | 28.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 30 | 9.5 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 58 | 16.3 | 17.0 |
| Rarely | 91 | 25.6 | 26.6 |
| Sometimes | 150 | 42.1 | 43.9 |
| Often | 43 | 12.1 | 12.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 3.9 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 36 | 10.1 | 11.4 |
| Rarely | 88 | 24.7 | 27.8 |
| Sometimes | 146 | 41.0 | 46.2 |
| Often | 46 | 12.9 | 14.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 40 | 11.2 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 42 | 11.8 | 13.4 |
| Rarely | 80 | 22.5 | 25.6 |
| Sometimes | 125 | 35.1 | 39.9 |
| Often | 66 | 18.5 | 21.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 43 | 12.1 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 91 | 15.6 | 16.1 |
| Rarely | 126 | 21.5 | 22.3 |
| Sometimes | 258 | 44.1 | 45.6 |
| Often | 90 | 15.4 | 15.9 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 19 | 3.2 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 62 | 10.6 | 11.9 |
| Rarely | 114 | 19.5 | 21.8 |
| Sometimes | 263 | 45.0 | 50.4 |
| Often | 82 | 14.0 | 15.7 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 63 | 10.8 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 68 | 11.6 | 12.9 |
| Rarely | 93 | 15.9 | 17.7 |
| Sometimes | 230 | 39.3 | 43.7 |
| Often | 133 | 22.7 | 25.3 |
| Scantron_Error | 2 | 0.3 | 0.4 |
| NA | 59 | 10.1 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 284 | 16.2 | 16.7 |
| Rarely | 503 | 28.7 | 29.6 |
| Sometimes | 726 | 41.4 | 42.8 |
| Often | 184 | 10.5 | 10.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 57 | 3.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 214 | 12.2 | 13.2 |
| Rarely | 437 | 24.9 | 27.0 |
| Sometimes | 763 | 43.5 | 47.2 |
| Often | 202 | 11.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 138 | 7.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 204 | 11.6 | 12.8 |
| Rarely | 322 | 18.4 | 20.1 |
| Sometimes | 708 | 40.4 | 44.3 |
| Often | 363 | 20.7 | 22.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 155 | 8.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3f1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 31.2 |
| Rarely | 2 | 12.5 | 12.5 |
| Sometimes | 8 | 50.0 | 50.0 |
| Often | 1 | 6.2 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 3 | 18.8 | 20.0 |
| Rarely | 3 | 18.8 | 20.0 |
| Sometimes | 8 | 50.0 | 53.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3f3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 3 | 18.8 | 20.0 |
| Sometimes | 4 | 25.0 | 26.7 |
| Often | 4 | 25.0 | 26.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3g1 <- as.factor(d[,"d3g1"])
levels(d3g1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3g1 <- ordered(d3g1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3g1)
new.d <- apply_labels(new.d, d3g1 = "called names or insulted-current")
temp.d <- data.frame (new.d, d3g1)
result<-questionr::freq(temp.d$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1247 | 35.1 | 36.3 |
| Rarely | 1180 | 33.2 | 34.4 |
| Sometimes | 869 | 24.4 | 25.3 |
| Often | 136 | 3.8 | 4.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 123 | 3.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3g2 <- as.factor(d[,"d3g2"])
levels(d3g2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3g2 <- ordered(d3g2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3g2)
new.d <- apply_labels(new.d, d3g2 = "called names or insulted-31 up")
temp.d <- data.frame (new.d, d3g2)
result<-questionr::freq(temp.d$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 815 | 22.9 | 25.0 |
| Rarely | 1177 | 33.1 | 36.1 |
| Sometimes | 1099 | 30.9 | 33.7 |
| Often | 171 | 4.8 | 5.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 295 | 8.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3g3 <- as.factor(d[,"d3g3"])
levels(d3g3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3g3 <- ordered(d3g3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3g3)
new.d <- apply_labels(new.d, d3g3 = "called names or insulted-child or young")
temp.d <- data.frame (new.d, d3g3)
result<-questionr::freq(temp.d$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 566 | 15.9 | 17.5 |
| Rarely | 836 | 23.5 | 25.8 |
| Sometimes | 1339 | 37.6 | 41.3 |
| Often | 497 | 14.0 | 15.3 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 316 | 8.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 125 | 38.9 | 39.7 |
| Rarely | 121 | 37.7 | 38.4 |
| Sometimes | 62 | 19.3 | 19.7 |
| Often | 7 | 2.2 | 2.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 62 | 19.3 | 19.9 |
| Rarely | 137 | 42.7 | 44.1 |
| Sometimes | 103 | 32.1 | 33.1 |
| Often | 9 | 2.8 | 2.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 32 | 10.0 | 10.3 |
| Rarely | 104 | 32.4 | 33.3 |
| Sometimes | 144 | 44.9 | 46.2 |
| Often | 32 | 10.0 | 10.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 50 | 23.8 | 24.4 |
| Rarely | 83 | 39.5 | 40.5 |
| Sometimes | 64 | 30.5 | 31.2 |
| Often | 8 | 3.8 | 3.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 32 | 15.2 | 16.3 |
| Rarely | 82 | 39.0 | 41.8 |
| Sometimes | 68 | 32.4 | 34.7 |
| Often | 14 | 6.7 | 7.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 30 | 14.3 | 15.3 |
| Rarely | 46 | 21.9 | 23.5 |
| Sometimes | 87 | 41.4 | 44.4 |
| Often | 33 | 15.7 | 16.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 96 | 30.5 | 31.8 |
| Rarely | 124 | 39.4 | 41.1 |
| Sometimes | 73 | 23.2 | 24.2 |
| Often | 9 | 2.9 | 3.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 62 | 19.7 | 21.2 |
| Rarely | 108 | 34.3 | 36.9 |
| Sometimes | 106 | 33.7 | 36.2 |
| Often | 17 | 5.4 | 5.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 22 | 7.0 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 44 | 14.0 | 15.1 |
| Rarely | 61 | 19.4 | 21.0 |
| Sometimes | 130 | 41.3 | 44.7 |
| Often | 56 | 17.8 | 19.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 114 | 32.0 | 33.1 |
| Rarely | 111 | 31.2 | 32.3 |
| Sometimes | 102 | 28.7 | 29.7 |
| Often | 17 | 4.8 | 4.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.4 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 80 | 22.5 | 24.8 |
| Rarely | 112 | 31.5 | 34.7 |
| Sometimes | 114 | 32.0 | 35.3 |
| Often | 17 | 4.8 | 5.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 33 | 9.3 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 64 | 18.0 | 20.2 |
| Rarely | 78 | 21.9 | 24.6 |
| Sometimes | 136 | 38.2 | 42.9 |
| Often | 39 | 11.0 | 12.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 39 | 11.0 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 189 | 32.3 | 34.0 |
| Rarely | 167 | 28.5 | 30.0 |
| Sometimes | 166 | 28.4 | 29.9 |
| Often | 34 | 5.8 | 6.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 29 | 5.0 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 122 | 20.9 | 23.7 |
| Rarely | 158 | 27.0 | 30.7 |
| Sometimes | 195 | 33.3 | 37.9 |
| Often | 39 | 6.7 | 7.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 71 | 12.1 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 92 | 15.7 | 17.9 |
| Rarely | 106 | 18.1 | 20.6 |
| Sometimes | 221 | 37.8 | 42.9 |
| Often | 96 | 16.4 | 18.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 70 | 12.0 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 669 | 38.1 | 39.4 |
| Rarely | 568 | 32.4 | 33.5 |
| Sometimes | 396 | 22.6 | 23.3 |
| Often | 61 | 3.5 | 3.6 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 58 | 3.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 453 | 25.8 | 28.1 |
| Rarely | 578 | 33.0 | 35.9 |
| Sometimes | 505 | 28.8 | 31.4 |
| Often | 74 | 4.2 | 4.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 144 | 8.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 301 | 17.2 | 18.9 |
| Rarely | 441 | 25.1 | 27.6 |
| Sometimes | 612 | 34.9 | 38.4 |
| Often | 239 | 13.6 | 15.0 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 159 | 9.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 25.0 |
| Rarely | 6 | 37.5 | 37.5 |
| Sometimes | 6 | 37.5 | 37.5 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 2 | 12.5 | 13.3 |
| Sometimes | 8 | 50.0 | 53.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 3 | 18.8 | 20.0 |
| Rarely | 0 | 0.0 | 0.0 |
| Sometimes | 9 | 56.2 | 60.0 |
| Often | 2 | 12.5 | 13.3 |
| Scantron_Error | 1 | 6.2 | 6.7 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3h1 <- as.factor(d[,"d3h1"])
levels(d3h1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3h1 <- ordered(d3h1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3h1)
new.d <- apply_labels(new.d, d3h1 = "threatened or harassed-current")
temp.d <- data.frame (new.d, d3h1)
result<-questionr::freq(temp.d$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1905 | 53.6 | 55.6 |
| Rarely | 1002 | 28.2 | 29.2 |
| Sometimes | 466 | 13.1 | 13.6 |
| Often | 52 | 1.5 | 1.5 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 130 | 3.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3h2 <- as.factor(d[,"d3h2"])
levels(d3h2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3h2 <- ordered(d3h2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3h2)
new.d <- apply_labels(new.d, d3h2 = "threatened or harassed-31 up")
temp.d <- data.frame (new.d, d3h2)
result<-questionr::freq(temp.d$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 1394 | 39.2 | 42.8 |
| Rarely | 1135 | 31.9 | 34.9 |
| Sometimes | 630 | 17.7 | 19.4 |
| Often | 92 | 2.6 | 2.8 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 303 | 8.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3h3 <- as.factor(d[,"d3h3"])
levels(d3h3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3h3 <- ordered(d3h3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3h3)
new.d <- apply_labels(new.d, d3h3 = "threatened or harassed-child or young")
temp.d <- data.frame (new.d, d3h3)
result<-questionr::freq(temp.d$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 1089 | 30.6 | 33.6 |
| Rarely | 944 | 26.5 | 29.1 |
| Sometimes | 931 | 26.2 | 28.7 |
| Often | 273 | 7.7 | 8.4 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 317 | 8.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 166 | 51.7 | 52.9 |
| Rarely | 106 | 33.0 | 33.8 |
| Sometimes | 38 | 11.8 | 12.1 |
| Often | 4 | 1.2 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 96 | 29.9 | 30.9 |
| Rarely | 143 | 44.5 | 46.0 |
| Sometimes | 62 | 19.3 | 19.9 |
| Often | 10 | 3.1 | 3.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 69 | 21.5 | 22.2 |
| Rarely | 115 | 35.8 | 37.0 |
| Sometimes | 109 | 34.0 | 35.0 |
| Often | 18 | 5.6 | 5.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 98 | 46.7 | 47.8 |
| Rarely | 68 | 32.4 | 33.2 |
| Sometimes | 34 | 16.2 | 16.6 |
| Often | 5 | 2.4 | 2.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 73 | 34.8 | 37.1 |
| Rarely | 74 | 35.2 | 37.6 |
| Sometimes | 41 | 19.5 | 20.8 |
| Often | 9 | 4.3 | 4.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 6.2 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 58 | 27.6 | 29.6 |
| Rarely | 57 | 27.1 | 29.1 |
| Sometimes | 63 | 30.0 | 32.1 |
| Often | 18 | 8.6 | 9.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 6.7 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 155 | 49.2 | 51.5 |
| Rarely | 102 | 32.4 | 33.9 |
| Sometimes | 37 | 11.7 | 12.3 |
| Often | 6 | 1.9 | 2.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 112 | 35.6 | 38.4 |
| Rarely | 109 | 34.6 | 37.3 |
| Sometimes | 62 | 19.7 | 21.2 |
| Often | 8 | 2.5 | 2.7 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 23 | 7.3 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 79 | 25.1 | 27.2 |
| Rarely | 81 | 25.7 | 27.9 |
| Sometimes | 94 | 29.8 | 32.4 |
| Often | 35 | 11.1 | 12.1 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 25 | 7.9 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 176 | 49.4 | 52.1 |
| Rarely | 107 | 30.1 | 31.7 |
| Sometimes | 50 | 14.0 | 14.8 |
| Often | 5 | 1.4 | 1.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 5.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 128 | 36.0 | 40.6 |
| Rarely | 117 | 32.9 | 37.1 |
| Sometimes | 59 | 16.6 | 18.7 |
| Often | 11 | 3.1 | 3.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 41 | 11.5 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 105 | 29.5 | 33.5 |
| Rarely | 98 | 27.5 | 31.3 |
| Sometimes | 90 | 25.3 | 28.8 |
| Often | 20 | 5.6 | 6.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 43 | 12.1 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 317 | 54.2 | 56.2 |
| Rarely | 149 | 25.5 | 26.4 |
| Sometimes | 86 | 14.7 | 15.2 |
| Often | 12 | 2.1 | 2.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 3.6 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 242 | 41.4 | 46.4 |
| Rarely | 152 | 26.0 | 29.1 |
| Sometimes | 108 | 18.5 | 20.7 |
| Often | 20 | 3.4 | 3.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 63 | 10.8 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 190 | 32.5 | 36.5 |
| Rarely | 146 | 25.0 | 28.0 |
| Sometimes | 134 | 22.9 | 25.7 |
| Often | 51 | 8.7 | 9.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 64 | 10.9 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 984 | 56.1 | 58.2 |
| Rarely | 466 | 26.6 | 27.6 |
| Sometimes | 219 | 12.5 | 13.0 |
| Often | 20 | 1.1 | 1.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 64 | 3.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 734 | 41.8 | 45.8 |
| Rarely | 538 | 30.7 | 33.6 |
| Sometimes | 295 | 16.8 | 18.4 |
| Often | 34 | 1.9 | 2.1 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 151 | 8.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 581 | 33.1 | 36.4 |
| Rarely | 446 | 25.4 | 28.0 |
| Sometimes | 435 | 24.8 | 27.3 |
| Often | 131 | 7.5 | 8.2 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 159 | 9.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3h1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 9 | 56.2 | 60.0 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 2 | 12.5 | 13.3 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 9 | 56.2 | 64.3 |
| Rarely | 2 | 12.5 | 14.3 |
| Sometimes | 3 | 18.8 | 21.4 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3h3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 7 | 43.8 | 50.0 |
| Rarely | 1 | 6.2 | 7.1 |
| Sometimes | 6 | 37.5 | 42.9 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3i1 <- as.factor(d[,"d3i1"])
levels(d3i1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3i1 <- ordered(d3i1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3i1)
new.d <- apply_labels(new.d, d3i1 = "be followed-current")
temp.d <- data.frame (new.d, d3i1)
result<-questionr::freq(temp.d$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1294 | 36.4 | 37.7 |
| Rarely | 952 | 26.8 | 27.8 |
| Sometimes | 932 | 26.2 | 27.2 |
| Often | 249 | 7.0 | 7.3 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 128 | 3.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3i2 <- as.factor(d[,"d3i2"])
levels(d3i2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3i2 <- ordered(d3i2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3i2)
new.d <- apply_labels(new.d, d3i2 = "be followed-31 up")
temp.d <- data.frame (new.d, d3i2)
result<-questionr::freq(temp.d$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 917 | 25.8 | 28.2 |
| Rarely | 888 | 25.0 | 27.3 |
| Sometimes | 1111 | 31.2 | 34.1 |
| Often | 338 | 9.5 | 10.4 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 302 | 8.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3i3 <- as.factor(d[,"d3i3"])
levels(d3i3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3i3 <- ordered(d3i3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3i3)
new.d <- apply_labels(new.d, d3i3 = "be followed-child or young")
temp.d <- data.frame (new.d, d3i3)
result<-questionr::freq(temp.d$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 773 | 21.7 | 23.9 |
| Rarely | 635 | 17.9 | 19.6 |
| Sometimes | 1133 | 31.9 | 35.0 |
| Often | 692 | 19.5 | 21.4 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 321 | 9.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 116 | 36.1 | 36.7 |
| Rarely | 80 | 24.9 | 25.3 |
| Sometimes | 90 | 28.0 | 28.5 |
| Often | 30 | 9.3 | 9.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 74 | 23.1 | 23.8 |
| Rarely | 93 | 29.0 | 29.9 |
| Sometimes | 108 | 33.6 | 34.7 |
| Often | 36 | 11.2 | 11.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 56 | 17.4 | 17.9 |
| Rarely | 75 | 23.4 | 24.0 |
| Sometimes | 126 | 39.3 | 40.4 |
| Often | 55 | 17.1 | 17.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 53 | 25.2 | 25.9 |
| Rarely | 61 | 29.0 | 29.8 |
| Sometimes | 75 | 35.7 | 36.6 |
| Often | 16 | 7.6 | 7.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 39 | 18.6 | 19.8 |
| Rarely | 48 | 22.9 | 24.4 |
| Sometimes | 82 | 39.0 | 41.6 |
| Often | 28 | 13.3 | 14.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 6.2 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 37 | 17.6 | 19.0 |
| Rarely | 32 | 15.2 | 16.4 |
| Sometimes | 71 | 33.8 | 36.4 |
| Often | 55 | 26.2 | 28.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 7.1 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 95 | 30.2 | 31.7 |
| Rarely | 95 | 30.2 | 31.7 |
| Sometimes | 80 | 25.4 | 26.7 |
| Often | 30 | 9.5 | 10.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.8 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 62 | 19.7 | 21.3 |
| Rarely | 83 | 26.3 | 28.5 |
| Sometimes | 102 | 32.4 | 35.1 |
| Often | 44 | 14.0 | 15.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 64 | 20.3 | 22.0 |
| Rarely | 51 | 16.2 | 17.5 |
| Sometimes | 92 | 29.2 | 31.6 |
| Often | 84 | 26.7 | 28.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 7.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 122 | 34.3 | 35.6 |
| Rarely | 104 | 29.2 | 30.3 |
| Sometimes | 92 | 25.8 | 26.8 |
| Often | 25 | 7.0 | 7.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 3.7 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 88 | 24.7 | 27.5 |
| Rarely | 94 | 26.4 | 29.4 |
| Sometimes | 109 | 30.6 | 34.1 |
| Often | 29 | 8.1 | 9.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 10.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 73 | 20.5 | 23.2 |
| Rarely | 77 | 21.6 | 24.4 |
| Sometimes | 107 | 30.1 | 34.0 |
| Often | 58 | 16.3 | 18.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 41 | 11.5 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 241 | 41.2 | 43.1 |
| Rarely | 123 | 21.0 | 22.0 |
| Sometimes | 152 | 26.0 | 27.2 |
| Often | 43 | 7.4 | 7.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 26 | 4.4 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 166 | 28.4 | 32.4 |
| Rarely | 119 | 20.3 | 23.2 |
| Sometimes | 176 | 30.1 | 34.3 |
| Often | 52 | 8.9 | 10.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 72 | 12.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 140 | 23.9 | 27.3 |
| Rarely | 77 | 13.2 | 15.0 |
| Sometimes | 188 | 32.1 | 36.6 |
| Often | 108 | 18.5 | 21.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 72 | 12.3 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 661 | 37.7 | 39.1 |
| Rarely | 483 | 27.5 | 28.6 |
| Sometimes | 441 | 25.1 | 26.1 |
| Often | 103 | 5.9 | 6.1 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 64 | 3.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 484 | 27.6 | 30.1 |
| Rarely | 445 | 25.4 | 27.7 |
| Sometimes | 532 | 30.3 | 33.1 |
| Often | 146 | 8.3 | 9.1 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 146 | 8.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 398 | 22.7 | 25.0 |
| Rarely | 321 | 18.3 | 20.1 |
| Sometimes | 543 | 31.0 | 34.0 |
| Often | 330 | 18.8 | 20.7 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 159 | 9.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3i1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 6 | 37.5 | 37.5 |
| Rarely | 6 | 37.5 | 37.5 |
| Sometimes | 2 | 12.5 | 12.5 |
| Often | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 4 | 25.0 | 26.7 |
| Rarely | 6 | 37.5 | 40.0 |
| Sometimes | 2 | 12.5 | 13.3 |
| Often | 3 | 18.8 | 20.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3i3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 5 | 31.2 | 33.3 |
| Rarely | 2 | 12.5 | 13.3 |
| Sometimes | 6 | 37.5 | 40.0 |
| Often | 2 | 12.5 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# 1
d3j1 <- as.factor(d[,"d3j1"])
levels(d3j1) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3j1 <- ordered(d3j1, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3j1)
new.d <- apply_labels(new.d, d3j1 = "How stressful-current")
temp.d <- data.frame (new.d, d3j1)
result<-questionr::freq(temp.d$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 1451 | 40.8 | 42.4 |
| Rarely | 1165 | 32.8 | 34.0 |
| Sometimes | 602 | 16.9 | 17.6 |
| Often | 206 | 5.8 | 6.0 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 132 | 3.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
#2
d3j2 <- as.factor(d[,"d3j2"])
levels(d3j2) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3j2 <- ordered(d3j2, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3j2)
new.d <- apply_labels(new.d, d3j2 = "How stressful-31 up")
temp.d <- data.frame (new.d, d3j2)
result<-questionr::freq(temp.d$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 1116 | 31.4 | 34.4 |
| Rarely | 1149 | 32.3 | 35.4 |
| Sometimes | 737 | 20.7 | 22.7 |
| Often | 245 | 6.9 | 7.5 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 309 | 8.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
#3
d3j3 <- as.factor(d[,"d3j3"])
levels(d3j3) <- list(Never="1",
Rarely="2",
Sometimes="3",
Often="4",
Scantron_Error="*")
d3j3 <- ordered(d3j3, c("Never","Rarely","Sometimes","Often","Scantron_Error"))
new.d <- data.frame(new.d, d3j3)
new.d <- apply_labels(new.d, d3j3 = "How stressful-child or young")
temp.d <- data.frame (new.d, d3j3)
result<-questionr::freq(temp.d$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 995 | 28.0 | 30.8 |
| Rarely | 1008 | 28.3 | 31.2 |
| Sometimes | 798 | 22.4 | 24.7 |
| Often | 428 | 12.0 | 13.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 328 | 9.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 91 | 28.3 | 28.7 |
| Rarely | 107 | 33.3 | 33.8 |
| Sometimes | 83 | 25.9 | 26.2 |
| Often | 36 | 11.2 | 11.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 62 | 19.3 | 19.9 |
| Rarely | 113 | 35.2 | 36.3 |
| Sometimes | 94 | 29.3 | 30.2 |
| Often | 42 | 13.1 | 13.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 56 | 17.4 | 17.9 |
| Rarely | 99 | 30.8 | 31.6 |
| Sometimes | 114 | 35.5 | 36.4 |
| Often | 44 | 13.7 | 14.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.5 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 72 | 34.3 | 35.3 |
| Rarely | 66 | 31.4 | 32.4 |
| Sometimes | 47 | 22.4 | 23.0 |
| Often | 19 | 9.0 | 9.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 58 | 27.6 | 29.9 |
| Rarely | 57 | 27.1 | 29.4 |
| Sometimes | 53 | 25.2 | 27.3 |
| Often | 26 | 12.4 | 13.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 7.6 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 55 | 26.2 | 28.6 |
| Rarely | 43 | 20.5 | 22.4 |
| Sometimes | 65 | 31.0 | 33.9 |
| Often | 29 | 13.8 | 15.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 8.6 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 105 | 33.3 | 35.1 |
| Rarely | 110 | 34.9 | 36.8 |
| Sometimes | 61 | 19.4 | 20.4 |
| Often | 23 | 7.3 | 7.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 16 | 5.1 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 78 | 24.8 | 26.9 |
| Rarely | 106 | 33.7 | 36.6 |
| Sometimes | 71 | 22.5 | 24.5 |
| Often | 35 | 11.1 | 12.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 7.9 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 73 | 23.2 | 25.3 |
| Rarely | 87 | 27.6 | 30.2 |
| Sometimes | 65 | 20.6 | 22.6 |
| Often | 63 | 20.0 | 21.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 27 | 8.6 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 143 | 40.2 | 42.3 |
| Rarely | 115 | 32.3 | 34.0 |
| Sometimes | 61 | 17.1 | 18.0 |
| Often | 19 | 5.3 | 5.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 18 | 5.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 108 | 30.3 | 34.0 |
| Rarely | 115 | 32.3 | 36.2 |
| Sometimes | 74 | 20.8 | 23.3 |
| Often | 21 | 5.9 | 6.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 38 | 10.7 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 97 | 27.2 | 31.0 |
| Rarely | 110 | 30.9 | 35.1 |
| Sometimes | 74 | 20.8 | 23.6 |
| Often | 32 | 9.0 | 10.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 43 | 12.1 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 245 | 41.9 | 43.8 |
| Rarely | 192 | 32.8 | 34.3 |
| Sometimes | 87 | 14.9 | 15.5 |
| Often | 36 | 6.2 | 6.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 179 | 30.6 | 34.7 |
| Rarely | 185 | 31.6 | 35.9 |
| Sometimes | 110 | 18.8 | 21.3 |
| Often | 42 | 7.2 | 8.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 69 | 11.8 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 158 | 27.0 | 30.6 |
| Rarely | 169 | 28.9 | 32.7 |
| Sometimes | 110 | 18.8 | 21.3 |
| Often | 80 | 13.7 | 15.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 68 | 11.6 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 785 | 44.8 | 46.4 |
| Rarely | 569 | 32.4 | 33.6 |
| Sometimes | 263 | 15.0 | 15.6 |
| Often | 73 | 4.2 | 4.3 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 63 | 3.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 622 | 35.5 | 38.8 |
| Rarely | 570 | 32.5 | 35.5 |
| Sometimes | 333 | 19.0 | 20.8 |
| Often | 78 | 4.4 | 4.9 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 150 | 8.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 547 | 31.2 | 34.4 |
| Rarely | 496 | 28.3 | 31.2 |
| Sometimes | 369 | 21.0 | 23.2 |
| Often | 179 | 10.2 | 11.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 163 | 9.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$d3j1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Current (from prostate cancer diagnosis to the present)")
| n | % | val% | |
|---|---|---|---|
| Never | 10 | 62.5 | 62.5 |
| Rarely | 6 | 37.5 | 37.5 |
| Sometimes | 0 | 0.0 | 0.0 |
| Often | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Age 31 up to just before prostate cancer diagnosis")
| n | % | val% | |
|---|---|---|---|
| Never | 9 | 56.2 | 60.0 |
| Rarely | 3 | 18.8 | 20.0 |
| Sometimes | 2 | 12.5 | 13.3 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$d3j3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Childhood or young adult life (up to age 30)")
| n | % | val% | |
|---|---|---|---|
| Never | 9 | 56.2 | 60.0 |
| Rarely | 4 | 25.0 | 26.7 |
| Sometimes | 1 | 6.2 | 6.7 |
| Often | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
# a. You’ve always felt that you could make of your life pretty much what you wanted to make of it.
d4a <- as.factor(d[,"d4a"])
levels(d4a) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4a <- ordered(d4a, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4a)
new.d <- apply_labels(new.d, d4a = "make life")
temp.d <- data.frame (new.d, d4a)
result<-questionr::freq(temp.d$d4a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. You’ve always felt that you could make of your life pretty much what you wanted to make of it.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1762 | 49.5 | 50.6 | 49.5 | 50.6 |
| Somewhat_Agree | 1383 | 38.9 | 39.8 | 88.4 | 90.4 |
| Somewhat_Disagree | 269 | 7.6 | 7.7 | 96.0 | 98.1 |
| Strongly_Disagree | 57 | 1.6 | 1.6 | 97.6 | 99.8 |
| Scantron_Error | 8 | 0.2 | 0.2 | 97.8 | 100.0 |
| NA | 78 | 2.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# b. Once you make up your mind to do something, you stay with it until the job is completely done.
d4b <- as.factor(d[,"d4b"])
levels(d4b) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4b <- ordered(d4b, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4b)
new.d <- apply_labels(new.d, d4b = "until job is done")
temp.d <- data.frame (new.d, d4b)
result<-questionr::freq(temp.d$d4b,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Once you make up your mind to do something, you stay with it until the job is completely done.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 2251 | 63.3 | 64.5 | 63.3 | 64.5 |
| Somewhat_Agree | 1092 | 30.7 | 31.3 | 94.0 | 95.8 |
| Somewhat_Disagree | 121 | 3.4 | 3.5 | 97.4 | 99.2 |
| Strongly_Disagree | 19 | 0.5 | 0.5 | 97.9 | 99.8 |
| Scantron_Error | 8 | 0.2 | 0.2 | 98.1 | 100.0 |
| NA | 66 | 1.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# c. You like doing things that other people thought could not be done.
d4c <- as.factor(d[,"d4c"])
levels(d4c) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4c <- ordered(d4c, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4c)
new.d <- apply_labels(new.d, d4c = "until job is done")
temp.d <- data.frame (new.d, d4c)
result<-questionr::freq(temp.d$d4c,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. You like doing things that other people thought could not be done.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1659 | 46.6 | 47.9 | 46.6 | 47.9 |
| Somewhat_Agree | 1384 | 38.9 | 40.0 | 85.5 | 87.9 |
| Somewhat_Disagree | 351 | 9.9 | 10.1 | 95.4 | 98.0 |
| Strongly_Disagree | 59 | 1.7 | 1.7 | 97.1 | 99.7 |
| Scantron_Error | 9 | 0.3 | 0.3 | 97.3 | 100.0 |
| NA | 95 | 2.7 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# d. When things don’t go the way you want them to, that just makes you work even harder.
d4d <- as.factor(d[,"d4d"])
levels(d4d) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4d <- ordered(d4d, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4d)
new.d <- apply_labels(new.d, d4d = "until job is done")
temp.d <- data.frame (new.d, d4d)
result<-questionr::freq(temp.d$d4d,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. When things don’t go the way you want them to, that just makes you work even harder.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1695 | 47.7 | 48.9 | 47.7 | 48.9 |
| Somewhat_Agree | 1421 | 39.9 | 41.0 | 87.6 | 89.9 |
| Somewhat_Disagree | 297 | 8.3 | 8.6 | 96.0 | 98.5 |
| Strongly_Disagree | 47 | 1.3 | 1.4 | 97.3 | 99.9 |
| Scantron_Error | 5 | 0.1 | 0.1 | 97.4 | 100.0 |
| NA | 92 | 2.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# e. Sometimes, you feel that if anything is going to be done right, you have to do it yourself.
d4e <- as.factor(d[,"d4e"])
levels(d4e) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4e <- ordered(d4e, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4e)
new.d <- apply_labels(new.d, d4e = "do it yourself")
temp.d <- data.frame (new.d, d4e)
result<-questionr::freq(temp.d$d4e,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. Sometimes, you feel that if anything is going to be done right, you have to do it yourself.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1489 | 41.9 | 42.8 | 41.9 | 42.8 |
| Somewhat_Agree | 1373 | 38.6 | 39.5 | 80.5 | 82.3 |
| Somewhat_Disagree | 506 | 14.2 | 14.5 | 94.7 | 96.8 |
| Strongly_Disagree | 105 | 3.0 | 3.0 | 97.6 | 99.9 |
| Scantron_Error | 5 | 0.1 | 0.1 | 97.8 | 100.0 |
| NA | 79 | 2.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# f. It’s not always easy, but you manage to find a way to do the things you really need to get done.
d4f <- as.factor(d[,"d4f"])
levels(d4f) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4f <- ordered(d4f, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4f)
new.d <- apply_labels(new.d, d4f = "not easy but get it done")
temp.d <- data.frame (new.d, d4f)
result<-questionr::freq(temp.d$d4f,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. It’s not always easy, but you manage to find a way to do the things you really need to get done.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 2258 | 63.5 | 64.8 | 63.5 | 64.8 |
| Somewhat_Agree | 1126 | 31.7 | 32.3 | 95.1 | 97.1 |
| Somewhat_Disagree | 72 | 2.0 | 2.1 | 97.2 | 99.2 |
| Strongly_Disagree | 22 | 0.6 | 0.6 | 97.8 | 99.8 |
| Scantron_Error | 7 | 0.2 | 0.2 | 98.0 | 100.0 |
| NA | 72 | 2.0 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# g. Very seldom have you been disappointed by the results of your hard work.
d4g <- as.factor(d[,"d4g"])
levels(d4g) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4g <- ordered(d4g, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4g)
new.d <- apply_labels(new.d, d4g = "seldom disappointed")
temp.d <- data.frame (new.d, d4g)
result<-questionr::freq(temp.d$d4g,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g. Very seldom have you been disappointed by the results of your hard work.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1262 | 35.5 | 36.4 | 35.5 | 36.4 |
| Somewhat_Agree | 1605 | 45.1 | 46.3 | 80.6 | 82.7 |
| Somewhat_Disagree | 458 | 12.9 | 13.2 | 93.5 | 96.0 |
| Strongly_Disagree | 137 | 3.9 | 4.0 | 97.3 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 97.4 | 100.0 |
| NA | 92 | 2.6 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# h. You feel you are the kind of individual who stands up for what he believes in, regardless of the consequences.
d4h <- as.factor(d[,"d4h"])
levels(d4h) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4h <- ordered(d4h, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4h)
new.d <- apply_labels(new.d, d4h = "stand up for believes")
temp.d <- data.frame (new.d, d4h)
result<-questionr::freq(temp.d$d4h,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "h. You feel you are the kind of individual who stands up for what he believes in, regardless of the consequences.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 2179 | 61.3 | 62.7 | 61.3 | 62.7 |
| Somewhat_Agree | 1110 | 31.2 | 31.9 | 92.5 | 94.6 |
| Somewhat_Disagree | 156 | 4.4 | 4.5 | 96.9 | 99.1 |
| Strongly_Disagree | 27 | 0.8 | 0.8 | 97.6 | 99.9 |
| Scantron_Error | 4 | 0.1 | 0.1 | 97.7 | 100.0 |
| NA | 81 | 2.3 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
# i. In the past, even when things got really tough, you never lost sight of your goals.
d4i <- as.factor(d[,"d4i"])
levels(d4i) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4i <- ordered(d4i, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4i)
new.d <- apply_labels(new.d, d4i = "tough but never lost")
temp.d <- data.frame (new.d, d4i)
result<-questionr::freq(temp.d$d4i,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "i. In the past, even when things got really tough, you never lost sight of your goals.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1998 | 56.2 | 57.4 | 56.2 | 57.4 |
| Somewhat_Agree | 1231 | 34.6 | 35.3 | 90.8 | 92.7 |
| Somewhat_Disagree | 215 | 6.0 | 6.2 | 96.8 | 98.9 |
| Strongly_Disagree | 31 | 0.9 | 0.9 | 97.7 | 99.8 |
| Scantron_Error | 8 | 0.2 | 0.2 | 97.9 | 100.0 |
| NA | 74 | 2.1 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
#j. It’s important for you to be able to do things the way you want to do them rather than the way other people want you to do them.
d4j <- as.factor(d[,"d4j"])
levels(d4j) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4j <- ordered(d4j, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4j)
new.d <- apply_labels(new.d, d4j = "the way you want to do matters")
temp.d <- data.frame (new.d, d4j)
result<-questionr::freq(temp.d$d4j,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "j. It’s important for you to be able to do things the way you want to do them rather than the way other people want you to do them.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1202 | 33.8 | 34.6 | 33.8 | 34.6 |
| Somewhat_Agree | 1396 | 39.2 | 40.1 | 73.0 | 74.7 |
| Somewhat_Disagree | 734 | 20.6 | 21.1 | 93.7 | 95.8 |
| Strongly_Disagree | 137 | 3.9 | 3.9 | 97.5 | 99.7 |
| Scantron_Error | 10 | 0.3 | 0.3 | 97.8 | 100.0 |
| NA | 78 | 2.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
#k. You don’t let your personal feelings get in the way of doing a job.
d4k <- as.factor(d[,"d4k"])
levels(d4k) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4k <- ordered(d4k, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4k)
new.d <- apply_labels(new.d, d4k = "personal feelings never get in the way of job")
temp.d <- data.frame (new.d, d4k)
result<-questionr::freq(temp.d$d4k,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "k. You don’t let your personal feelings get in the way of doing a job.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1856 | 52.2 | 53.3 | 52.2 | 53.3 |
| Somewhat_Agree | 1309 | 36.8 | 37.6 | 89.0 | 90.8 |
| Somewhat_Disagree | 251 | 7.1 | 7.2 | 96.0 | 98.0 |
| Strongly_Disagree | 63 | 1.8 | 1.8 | 97.8 | 99.8 |
| Scantron_Error | 6 | 0.2 | 0.2 | 98.0 | 100.0 |
| NA | 72 | 2.0 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
#l. Hard work has really helped you to get ahead in life.
d4l <- as.factor(d[,"d4l"])
levels(d4l) <- list(Strongly_Agree ="1",
Somewhat_Agree="2",
Somewhat_Disagree="3",
Strongly_Disagree="4",
Scantron_Error="*")
d4l <- ordered(d4l, c("Strongly_Agree","Somewhat_Agree","Somewhat_Disagree","Strongly_Disagree","Scantron_Error"))
new.d <- data.frame(new.d, d4l)
new.d <- apply_labels(new.d, d4l = "hard work helps")
temp.d <- data.frame (new.d, d4l)
result<-questionr::freq(temp.d$d4l,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "l. Hard work has really helped you to get ahead in life.")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 2357 | 66.3 | 67.7 | 66.3 | 67.7 |
| Somewhat_Agree | 887 | 24.9 | 25.5 | 91.2 | 93.2 |
| Somewhat_Disagree | 183 | 5.1 | 5.3 | 96.3 | 98.4 |
| Strongly_Disagree | 52 | 1.5 | 1.5 | 97.8 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 97.9 | 100.0 |
| NA | 76 | 2.1 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 151 | 47.0 | 47.5 | 47.0 | 47.5 |
| Somewhat_Agree | 136 | 42.4 | 42.8 | 89.4 | 90.3 |
| Somewhat_Disagree | 25 | 7.8 | 7.9 | 97.2 | 98.1 |
| Strongly_Disagree | 6 | 1.9 | 1.9 | 99.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.1 | 100.0 |
| NA | 3 | 0.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 193 | 60.1 | 60.3 | 60.1 | 60.3 |
| Somewhat_Agree | 109 | 34.0 | 34.1 | 94.1 | 94.4 |
| Somewhat_Disagree | 16 | 5.0 | 5.0 | 99.1 | 99.4 |
| Strongly_Disagree | 2 | 0.6 | 0.6 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 140 | 43.6 | 43.8 | 43.6 | 43.8 |
| Somewhat_Agree | 140 | 43.6 | 43.8 | 87.2 | 87.5 |
| Somewhat_Disagree | 35 | 10.9 | 10.9 | 98.1 | 98.4 |
| Strongly_Disagree | 4 | 1.2 | 1.2 | 99.4 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 145 | 45.2 | 45.5 | 45.2 | 45.5 |
| Somewhat_Agree | 142 | 44.2 | 44.5 | 89.4 | 90.0 |
| Somewhat_Disagree | 30 | 9.3 | 9.4 | 98.8 | 99.4 |
| Strongly_Disagree | 2 | 0.6 | 0.6 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 140 | 43.6 | 43.8 | 43.6 | 43.8 |
| Somewhat_Agree | 125 | 38.9 | 39.1 | 82.6 | 82.8 |
| Somewhat_Disagree | 47 | 14.6 | 14.7 | 97.2 | 97.5 |
| Strongly_Disagree | 8 | 2.5 | 2.5 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 201 | 62.6 | 63.2 | 62.6 | 63.2 |
| Somewhat_Agree | 110 | 34.3 | 34.6 | 96.9 | 97.8 |
| Somewhat_Disagree | 5 | 1.6 | 1.6 | 98.4 | 99.4 |
| Strongly_Disagree | 1 | 0.3 | 0.3 | 98.8 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.1 | 100.0 |
| NA | 3 | 0.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 101 | 31.5 | 31.7 | 31.5 | 31.7 |
| Somewhat_Agree | 156 | 48.6 | 48.9 | 80.1 | 80.6 |
| Somewhat_Disagree | 49 | 15.3 | 15.4 | 95.3 | 95.9 |
| Strongly_Disagree | 13 | 4.0 | 4.1 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 202 | 62.9 | 63.1 | 62.9 | 63.1 |
| Somewhat_Agree | 103 | 32.1 | 32.2 | 95.0 | 95.3 |
| Somewhat_Disagree | 13 | 4.0 | 4.1 | 99.1 | 99.4 |
| Strongly_Disagree | 2 | 0.6 | 0.6 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 171 | 53.3 | 53.6 | 53.3 | 53.6 |
| Somewhat_Agree | 126 | 39.3 | 39.5 | 92.5 | 93.1 |
| Somewhat_Disagree | 21 | 6.5 | 6.6 | 99.1 | 99.7 |
| Strongly_Disagree | 1 | 0.3 | 0.3 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 100 | 31.2 | 31.2 | 31.2 | 31.2 |
| Somewhat_Agree | 136 | 42.4 | 42.5 | 73.5 | 73.8 |
| Somewhat_Disagree | 75 | 23.4 | 23.4 | 96.9 | 97.2 |
| Strongly_Disagree | 9 | 2.8 | 2.8 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 155 | 48.3 | 48.4 | 48.3 | 48.4 |
| Somewhat_Agree | 131 | 40.8 | 40.9 | 89.1 | 89.4 |
| Somewhat_Disagree | 30 | 9.3 | 9.4 | 98.4 | 98.8 |
| Strongly_Disagree | 4 | 1.2 | 1.2 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 213 | 66.4 | 66.6 | 66.4 | 66.6 |
| Somewhat_Agree | 82 | 25.5 | 25.6 | 91.9 | 92.2 |
| Somewhat_Disagree | 21 | 6.5 | 6.6 | 98.4 | 98.8 |
| Strongly_Disagree | 4 | 1.2 | 1.2 | 99.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.7 | 100.0 |
| NA | 1 | 0.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 97 | 46.2 | 46.6 | 46.2 | 46.6 |
| Somewhat_Agree | 87 | 41.4 | 41.8 | 87.6 | 88.5 |
| Somewhat_Disagree | 19 | 9.0 | 9.1 | 96.7 | 97.6 |
| Strongly_Disagree | 5 | 2.4 | 2.4 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 123 | 58.6 | 59.1 | 58.6 | 59.1 |
| Somewhat_Agree | 77 | 36.7 | 37.0 | 95.2 | 96.2 |
| Somewhat_Disagree | 7 | 3.3 | 3.4 | 98.6 | 99.5 |
| Strongly_Disagree | 1 | 0.5 | 0.5 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 102 | 48.6 | 48.8 | 48.6 | 48.8 |
| Somewhat_Agree | 86 | 41.0 | 41.1 | 89.5 | 90.0 |
| Somewhat_Disagree | 19 | 9.0 | 9.1 | 98.6 | 99.0 |
| Strongly_Disagree | 2 | 1.0 | 1.0 | 99.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.5 | 100.0 |
| NA | 1 | 0.5 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 89 | 42.4 | 42.8 | 42.4 | 42.8 |
| Somewhat_Agree | 104 | 49.5 | 50.0 | 91.9 | 92.8 |
| Somewhat_Disagree | 14 | 6.7 | 6.7 | 98.6 | 99.5 |
| Strongly_Disagree | 1 | 0.5 | 0.5 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 80 | 38.1 | 38.3 | 38.1 | 38.3 |
| Somewhat_Agree | 88 | 41.9 | 42.1 | 80.0 | 80.4 |
| Somewhat_Disagree | 34 | 16.2 | 16.3 | 96.2 | 96.7 |
| Strongly_Disagree | 7 | 3.3 | 3.3 | 99.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.5 | 100.0 |
| NA | 1 | 0.5 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 135 | 64.3 | 64.9 | 64.3 | 64.9 |
| Somewhat_Agree | 66 | 31.4 | 31.7 | 95.7 | 96.6 |
| Somewhat_Disagree | 4 | 1.9 | 1.9 | 97.6 | 98.6 |
| Strongly_Disagree | 2 | 1.0 | 1.0 | 98.6 | 99.5 |
| Scantron_Error | 1 | 0.5 | 0.5 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 63 | 30.0 | 30.6 | 30.0 | 30.6 |
| Somewhat_Agree | 105 | 50.0 | 51.0 | 80.0 | 81.6 |
| Somewhat_Disagree | 30 | 14.3 | 14.6 | 94.3 | 96.1 |
| Strongly_Disagree | 8 | 3.8 | 3.9 | 98.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.1 | 100.0 |
| NA | 4 | 1.9 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 119 | 56.7 | 57.2 | 56.7 | 57.2 |
| Somewhat_Agree | 75 | 35.7 | 36.1 | 92.4 | 93.3 |
| Somewhat_Disagree | 12 | 5.7 | 5.8 | 98.1 | 99.0 |
| Strongly_Disagree | 2 | 1.0 | 1.0 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 114 | 54.3 | 54.5 | 54.3 | 54.5 |
| Somewhat_Agree | 81 | 38.6 | 38.8 | 92.9 | 93.3 |
| Somewhat_Disagree | 11 | 5.2 | 5.3 | 98.1 | 98.6 |
| Strongly_Disagree | 3 | 1.4 | 1.4 | 99.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.5 | 100.0 |
| NA | 1 | 0.5 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 63 | 30.0 | 30.1 | 30.0 | 30.1 |
| Somewhat_Agree | 87 | 41.4 | 41.6 | 71.4 | 71.8 |
| Somewhat_Disagree | 52 | 24.8 | 24.9 | 96.2 | 96.7 |
| Strongly_Disagree | 7 | 3.3 | 3.3 | 99.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.5 | 100.0 |
| NA | 1 | 0.5 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 93 | 44.3 | 44.7 | 44.3 | 44.7 |
| Somewhat_Agree | 92 | 43.8 | 44.2 | 88.1 | 88.9 |
| Somewhat_Disagree | 22 | 10.5 | 10.6 | 98.6 | 99.5 |
| Strongly_Disagree | 1 | 0.5 | 0.5 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 131 | 62.4 | 63.0 | 62.4 | 63.0 |
| Somewhat_Agree | 63 | 30.0 | 30.3 | 92.4 | 93.3 |
| Somewhat_Disagree | 12 | 5.7 | 5.8 | 98.1 | 99.0 |
| Strongly_Disagree | 2 | 1.0 | 1.0 | 99.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.0 | 100.0 |
| NA | 2 | 1.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 150 | 47.6 | 49.5 | 47.6 | 49.5 |
| Somewhat_Agree | 113 | 35.9 | 37.3 | 83.5 | 86.8 |
| Somewhat_Disagree | 34 | 10.8 | 11.2 | 94.3 | 98.0 |
| Strongly_Disagree | 6 | 1.9 | 2.0 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 189 | 60.0 | 62.2 | 60.0 | 62.2 |
| Somewhat_Agree | 92 | 29.2 | 30.3 | 89.2 | 92.4 |
| Somewhat_Disagree | 19 | 6.0 | 6.2 | 95.2 | 98.7 |
| Strongly_Disagree | 3 | 1.0 | 1.0 | 96.2 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 96.5 | 100.0 |
| NA | 11 | 3.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 141 | 44.8 | 47.2 | 44.8 | 47.2 |
| Somewhat_Agree | 125 | 39.7 | 41.8 | 84.4 | 89.0 |
| Somewhat_Disagree | 27 | 8.6 | 9.0 | 93.0 | 98.0 |
| Strongly_Disagree | 6 | 1.9 | 2.0 | 94.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.9 | 100.0 |
| NA | 16 | 5.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 141 | 44.8 | 46.7 | 44.8 | 46.7 |
| Somewhat_Agree | 133 | 42.2 | 44.0 | 87.0 | 90.7 |
| Somewhat_Disagree | 23 | 7.3 | 7.6 | 94.3 | 98.3 |
| Strongly_Disagree | 5 | 1.6 | 1.7 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 115 | 36.5 | 38.1 | 36.5 | 38.1 |
| Somewhat_Agree | 128 | 40.6 | 42.4 | 77.1 | 80.5 |
| Somewhat_Disagree | 49 | 15.6 | 16.2 | 92.7 | 96.7 |
| Strongly_Disagree | 10 | 3.2 | 3.3 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 191 | 60.6 | 63.0 | 60.6 | 63.0 |
| Somewhat_Agree | 107 | 34.0 | 35.3 | 94.6 | 98.3 |
| Somewhat_Disagree | 5 | 1.6 | 1.7 | 96.2 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 116 | 36.8 | 38.4 | 36.8 | 38.4 |
| Somewhat_Agree | 133 | 42.2 | 44.0 | 79.0 | 82.5 |
| Somewhat_Disagree | 47 | 14.9 | 15.6 | 94.0 | 98.0 |
| Strongly_Disagree | 6 | 1.9 | 2.0 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 179 | 56.8 | 59.1 | 56.8 | 59.1 |
| Somewhat_Agree | 106 | 33.7 | 35.0 | 90.5 | 94.1 |
| Somewhat_Disagree | 15 | 4.8 | 5.0 | 95.2 | 99.0 |
| Strongly_Disagree | 3 | 1.0 | 1.0 | 96.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 174 | 55.2 | 57.6 | 55.2 | 57.6 |
| Somewhat_Agree | 105 | 33.3 | 34.8 | 88.6 | 92.4 |
| Somewhat_Disagree | 22 | 7.0 | 7.3 | 95.6 | 99.7 |
| Strongly_Disagree | 1 | 0.3 | 0.3 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 90 | 28.6 | 29.7 | 28.6 | 29.7 |
| Somewhat_Agree | 121 | 38.4 | 39.9 | 67.0 | 69.6 |
| Somewhat_Disagree | 76 | 24.1 | 25.1 | 91.1 | 94.7 |
| Strongly_Disagree | 15 | 4.8 | 5.0 | 95.9 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 96.2 | 100.0 |
| NA | 12 | 3.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 155 | 49.2 | 51.3 | 49.2 | 51.3 |
| Somewhat_Agree | 117 | 37.1 | 38.7 | 86.3 | 90.1 |
| Somewhat_Disagree | 27 | 8.6 | 8.9 | 94.9 | 99.0 |
| Strongly_Disagree | 3 | 1.0 | 1.0 | 95.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.9 | 100.0 |
| NA | 13 | 4.1 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 199 | 63.2 | 65.5 | 63.2 | 65.5 |
| Somewhat_Agree | 81 | 25.7 | 26.6 | 88.9 | 92.1 |
| Somewhat_Disagree | 19 | 6.0 | 6.2 | 94.9 | 98.4 |
| Strongly_Disagree | 5 | 1.6 | 1.6 | 96.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.5 | 100.0 |
| NA | 11 | 3.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 168 | 47.2 | 47.6 | 47.2 | 47.6 |
| Somewhat_Agree | 143 | 40.2 | 40.5 | 87.4 | 88.1 |
| Somewhat_Disagree | 33 | 9.3 | 9.3 | 96.6 | 97.5 |
| Strongly_Disagree | 8 | 2.2 | 2.3 | 98.9 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.2 | 100.0 |
| NA | 3 | 0.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 221 | 62.1 | 62.4 | 62.1 | 62.4 |
| Somewhat_Agree | 120 | 33.7 | 33.9 | 95.8 | 96.3 |
| Somewhat_Disagree | 11 | 3.1 | 3.1 | 98.9 | 99.4 |
| Strongly_Disagree | 1 | 0.3 | 0.3 | 99.2 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 155 | 43.5 | 44.5 | 43.5 | 44.5 |
| Somewhat_Agree | 145 | 40.7 | 41.7 | 84.3 | 86.2 |
| Somewhat_Disagree | 39 | 11.0 | 11.2 | 95.2 | 97.4 |
| Strongly_Disagree | 8 | 2.2 | 2.3 | 97.5 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 97.8 | 100.0 |
| NA | 8 | 2.2 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 144 | 40.4 | 41.1 | 40.4 | 41.1 |
| Somewhat_Agree | 154 | 43.3 | 44.0 | 83.7 | 85.1 |
| Somewhat_Disagree | 44 | 12.4 | 12.6 | 96.1 | 97.7 |
| Strongly_Disagree | 7 | 2.0 | 2.0 | 98.0 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 98.3 | 100.0 |
| NA | 6 | 1.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 146 | 41.0 | 41.7 | 41.0 | 41.7 |
| Somewhat_Agree | 140 | 39.3 | 40.0 | 80.3 | 81.7 |
| Somewhat_Disagree | 52 | 14.6 | 14.9 | 94.9 | 96.6 |
| Strongly_Disagree | 12 | 3.4 | 3.4 | 98.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.3 | 100.0 |
| NA | 6 | 1.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 207 | 58.1 | 58.5 | 58.1 | 58.5 |
| Somewhat_Agree | 136 | 38.2 | 38.4 | 96.3 | 96.9 |
| Somewhat_Disagree | 11 | 3.1 | 3.1 | 99.4 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 137 | 38.5 | 38.9 | 38.5 | 38.9 |
| Somewhat_Agree | 154 | 43.3 | 43.8 | 81.7 | 82.7 |
| Somewhat_Disagree | 48 | 13.5 | 13.6 | 95.2 | 96.3 |
| Strongly_Disagree | 13 | 3.7 | 3.7 | 98.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.9 | 100.0 |
| NA | 4 | 1.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 225 | 63.2 | 63.6 | 63.2 | 63.6 |
| Somewhat_Agree | 108 | 30.3 | 30.5 | 93.5 | 94.1 |
| Somewhat_Disagree | 18 | 5.1 | 5.1 | 98.6 | 99.2 |
| Strongly_Disagree | 3 | 0.8 | 0.8 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 189 | 53.1 | 53.5 | 53.1 | 53.5 |
| Somewhat_Agree | 136 | 38.2 | 38.5 | 91.3 | 92.1 |
| Somewhat_Disagree | 20 | 5.6 | 5.7 | 96.9 | 97.7 |
| Strongly_Disagree | 7 | 2.0 | 2.0 | 98.9 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.2 | 100.0 |
| NA | 3 | 0.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 121 | 34.0 | 34.5 | 34.0 | 34.5 |
| Somewhat_Agree | 143 | 40.2 | 40.7 | 74.2 | 75.2 |
| Somewhat_Disagree | 71 | 19.9 | 20.2 | 94.1 | 95.4 |
| Strongly_Disagree | 15 | 4.2 | 4.3 | 98.3 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 98.6 | 100.0 |
| NA | 5 | 1.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 187 | 52.5 | 52.8 | 52.5 | 52.8 |
| Somewhat_Agree | 133 | 37.4 | 37.6 | 89.9 | 90.4 |
| Somewhat_Disagree | 25 | 7.0 | 7.1 | 96.9 | 97.5 |
| Strongly_Disagree | 8 | 2.2 | 2.3 | 99.2 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 215 | 60.4 | 60.7 | 60.4 | 60.7 |
| Somewhat_Agree | 106 | 29.8 | 29.9 | 90.2 | 90.7 |
| Somewhat_Disagree | 23 | 6.5 | 6.5 | 96.6 | 97.2 |
| Strongly_Disagree | 10 | 2.8 | 2.8 | 99.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 99.4 | 100.0 |
| NA | 2 | 0.6 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 293 | 50.1 | 51.6 | 50.1 | 51.6 |
| Somewhat_Agree | 219 | 37.4 | 38.6 | 87.5 | 90.1 |
| Somewhat_Disagree | 46 | 7.9 | 8.1 | 95.4 | 98.2 |
| Strongly_Disagree | 10 | 1.7 | 1.8 | 97.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.1 | 100.0 |
| NA | 17 | 2.9 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 379 | 64.8 | 65.9 | 64.8 | 65.9 |
| Somewhat_Agree | 171 | 29.2 | 29.7 | 94.0 | 95.7 |
| Somewhat_Disagree | 19 | 3.2 | 3.3 | 97.3 | 99.0 |
| Strongly_Disagree | 6 | 1.0 | 1.0 | 98.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.3 | 100.0 |
| NA | 10 | 1.7 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 288 | 49.2 | 50.4 | 49.2 | 50.4 |
| Somewhat_Agree | 213 | 36.4 | 37.3 | 85.6 | 87.7 |
| Somewhat_Disagree | 56 | 9.6 | 9.8 | 95.2 | 97.5 |
| Strongly_Disagree | 13 | 2.2 | 2.3 | 97.4 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 97.6 | 100.0 |
| NA | 14 | 2.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 302 | 51.6 | 53.4 | 51.6 | 53.4 |
| Somewhat_Agree | 210 | 35.9 | 37.1 | 87.5 | 90.5 |
| Somewhat_Disagree | 44 | 7.5 | 7.8 | 95.0 | 98.2 |
| Strongly_Disagree | 10 | 1.7 | 1.8 | 96.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.8 | 100.0 |
| NA | 19 | 3.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 273 | 46.7 | 47.6 | 46.7 | 47.6 |
| Somewhat_Agree | 201 | 34.4 | 35.1 | 81.0 | 82.7 |
| Somewhat_Disagree | 82 | 14.0 | 14.3 | 95.0 | 97.0 |
| Strongly_Disagree | 16 | 2.7 | 2.8 | 97.8 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 97.9 | 100.0 |
| NA | 12 | 2.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 377 | 64.4 | 65.9 | 64.4 | 65.9 |
| Somewhat_Agree | 177 | 30.3 | 30.9 | 94.7 | 96.9 |
| Somewhat_Disagree | 10 | 1.7 | 1.7 | 96.4 | 98.6 |
| Strongly_Disagree | 6 | 1.0 | 1.0 | 97.4 | 99.7 |
| Scantron_Error | 2 | 0.3 | 0.3 | 97.8 | 100.0 |
| NA | 13 | 2.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 232 | 39.7 | 40.8 | 39.7 | 40.8 |
| Somewhat_Agree | 238 | 40.7 | 41.8 | 80.3 | 82.6 |
| Somewhat_Disagree | 67 | 11.5 | 11.8 | 91.8 | 94.4 |
| Strongly_Disagree | 32 | 5.5 | 5.6 | 97.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.3 | 100.0 |
| NA | 16 | 2.7 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 368 | 62.9 | 64.7 | 62.9 | 64.7 |
| Somewhat_Agree | 161 | 27.5 | 28.3 | 90.4 | 93.0 |
| Somewhat_Disagree | 32 | 5.5 | 5.6 | 95.9 | 98.6 |
| Strongly_Disagree | 8 | 1.4 | 1.4 | 97.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.3 | 100.0 |
| NA | 16 | 2.7 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 352 | 60.2 | 61.4 | 60.2 | 61.4 |
| Somewhat_Agree | 178 | 30.4 | 31.1 | 90.6 | 92.5 |
| Somewhat_Disagree | 32 | 5.5 | 5.6 | 96.1 | 98.1 |
| Strongly_Disagree | 9 | 1.5 | 1.6 | 97.6 | 99.7 |
| Scantron_Error | 2 | 0.3 | 0.3 | 97.9 | 100.0 |
| NA | 12 | 2.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 223 | 38.1 | 39.1 | 38.1 | 39.1 |
| Somewhat_Agree | 222 | 37.9 | 38.9 | 76.1 | 77.9 |
| Somewhat_Disagree | 101 | 17.3 | 17.7 | 93.3 | 95.6 |
| Strongly_Disagree | 23 | 3.9 | 4.0 | 97.3 | 99.6 |
| Scantron_Error | 2 | 0.3 | 0.4 | 97.6 | 100.0 |
| NA | 14 | 2.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 334 | 57.1 | 58.3 | 57.1 | 58.3 |
| Somewhat_Agree | 183 | 31.3 | 31.9 | 88.4 | 90.2 |
| Somewhat_Disagree | 41 | 7.0 | 7.2 | 95.4 | 97.4 |
| Strongly_Disagree | 15 | 2.6 | 2.6 | 97.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.9 | 100.0 |
| NA | 12 | 2.1 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 406 | 69.4 | 71.4 | 69.4 | 71.4 |
| Somewhat_Agree | 122 | 20.9 | 21.4 | 90.3 | 92.8 |
| Somewhat_Disagree | 27 | 4.6 | 4.7 | 94.9 | 97.5 |
| Strongly_Disagree | 14 | 2.4 | 2.5 | 97.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.3 | 100.0 |
| NA | 16 | 2.7 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 894 | 51.0 | 52.2 | 51.0 | 52.2 |
| Somewhat_Agree | 679 | 38.7 | 39.6 | 89.7 | 91.8 |
| Somewhat_Disagree | 112 | 6.4 | 6.5 | 96.1 | 98.3 |
| Strongly_Disagree | 22 | 1.3 | 1.3 | 97.3 | 99.6 |
| Scantron_Error | 7 | 0.4 | 0.4 | 97.7 | 100.0 |
| NA | 40 | 2.3 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1138 | 64.9 | 66.4 | 64.9 | 66.4 |
| Somewhat_Agree | 515 | 29.4 | 30.0 | 94.2 | 96.4 |
| Somewhat_Disagree | 49 | 2.8 | 2.9 | 97.0 | 99.3 |
| Strongly_Disagree | 6 | 0.3 | 0.4 | 97.4 | 99.6 |
| Scantron_Error | 6 | 0.3 | 0.4 | 97.7 | 100.0 |
| NA | 40 | 2.3 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 828 | 47.2 | 48.7 | 47.2 | 48.7 |
| Somewhat_Agree | 670 | 38.2 | 39.4 | 85.4 | 88.1 |
| Somewhat_Disagree | 170 | 9.7 | 10.0 | 95.1 | 98.1 |
| Strongly_Disagree | 26 | 1.5 | 1.5 | 96.6 | 99.6 |
| Scantron_Error | 6 | 0.3 | 0.4 | 96.9 | 100.0 |
| NA | 54 | 3.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 868 | 49.5 | 50.9 | 49.5 | 50.9 |
| Somewhat_Agree | 671 | 38.3 | 39.4 | 87.7 | 90.3 |
| Somewhat_Disagree | 140 | 8.0 | 8.2 | 95.7 | 98.5 |
| Strongly_Disagree | 21 | 1.2 | 1.2 | 96.9 | 99.8 |
| Scantron_Error | 4 | 0.2 | 0.2 | 97.1 | 100.0 |
| NA | 50 | 2.9 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 729 | 41.6 | 42.7 | 41.6 | 42.7 |
| Somewhat_Agree | 684 | 39.0 | 40.0 | 80.6 | 82.7 |
| Somewhat_Disagree | 239 | 13.6 | 14.0 | 94.2 | 96.7 |
| Strongly_Disagree | 52 | 3.0 | 3.0 | 97.1 | 99.8 |
| Scantron_Error | 4 | 0.2 | 0.2 | 97.4 | 100.0 |
| NA | 46 | 2.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1139 | 64.9 | 66.5 | 64.9 | 66.5 |
| Somewhat_Agree | 523 | 29.8 | 30.5 | 94.8 | 97.0 |
| Somewhat_Disagree | 36 | 2.1 | 2.1 | 96.8 | 99.1 |
| Strongly_Disagree | 13 | 0.7 | 0.8 | 97.5 | 99.8 |
| Scantron_Error | 3 | 0.2 | 0.2 | 97.7 | 100.0 |
| NA | 40 | 2.3 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 604 | 34.4 | 35.5 | 34.4 | 35.5 |
| Somewhat_Agree | 813 | 46.4 | 47.8 | 80.8 | 83.3 |
| Somewhat_Disagree | 216 | 12.3 | 12.7 | 93.1 | 96.0 |
| Strongly_Disagree | 65 | 3.7 | 3.8 | 96.8 | 99.8 |
| Scantron_Error | 3 | 0.2 | 0.2 | 97.0 | 100.0 |
| NA | 53 | 3.0 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1076 | 61.3 | 63.1 | 61.3 | 63.1 |
| Somewhat_Agree | 551 | 31.4 | 32.3 | 92.8 | 95.4 |
| Somewhat_Disagree | 66 | 3.8 | 3.9 | 96.5 | 99.2 |
| Strongly_Disagree | 9 | 0.5 | 0.5 | 97.0 | 99.8 |
| Scantron_Error | 4 | 0.2 | 0.2 | 97.3 | 100.0 |
| NA | 48 | 2.7 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 990 | 56.4 | 57.9 | 56.4 | 57.9 |
| Somewhat_Agree | 599 | 34.2 | 35.0 | 90.6 | 92.9 |
| Somewhat_Disagree | 107 | 6.1 | 6.3 | 96.7 | 99.1 |
| Strongly_Disagree | 10 | 0.6 | 0.6 | 97.3 | 99.7 |
| Scantron_Error | 5 | 0.3 | 0.3 | 97.5 | 100.0 |
| NA | 43 | 2.5 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 597 | 34.0 | 34.9 | 34.0 | 34.9 |
| Somewhat_Agree | 686 | 39.1 | 40.1 | 73.1 | 75.1 |
| Somewhat_Disagree | 352 | 20.1 | 20.6 | 93.2 | 95.7 |
| Strongly_Disagree | 68 | 3.9 | 4.0 | 97.1 | 99.6 |
| Scantron_Error | 6 | 0.3 | 0.4 | 97.4 | 100.0 |
| NA | 45 | 2.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 925 | 52.7 | 54.0 | 52.7 | 54.0 |
| Somewhat_Agree | 645 | 36.8 | 37.7 | 89.5 | 91.7 |
| Somewhat_Disagree | 106 | 6.0 | 6.2 | 95.6 | 97.9 |
| Strongly_Disagree | 31 | 1.8 | 1.8 | 97.3 | 99.7 |
| Scantron_Error | 5 | 0.3 | 0.3 | 97.6 | 100.0 |
| NA | 42 | 2.4 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 1185 | 67.6 | 69.3 | 67.6 | 69.3 |
| Somewhat_Agree | 428 | 24.4 | 25.0 | 92.0 | 94.3 |
| Somewhat_Disagree | 78 | 4.4 | 4.6 | 96.4 | 98.9 |
| Strongly_Disagree | 17 | 1.0 | 1.0 | 97.4 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 97.5 | 100.0 |
| NA | 44 | 2.5 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 9 | 56.2 | 60 | 56.2 | 60 |
| Somewhat_Agree | 6 | 37.5 | 40 | 93.8 | 100 |
| Somewhat_Disagree | 0 | 0.0 | 0 | 93.8 | 100 |
| Strongly_Disagree | 0 | 0.0 | 0 | 93.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 93.8 | 100 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 8 | 50 | 50 | 50 | 50 |
| Somewhat_Agree | 8 | 50 | 50 | 100 | 100 |
| Somewhat_Disagree | 0 | 0 | 0 | 100 | 100 |
| Strongly_Disagree | 0 | 0 | 0 | 100 | 100 |
| Scantron_Error | 0 | 0 | 0 | 100 | 100 |
| Total | 16 | 100 | 100 | 100 | 100 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 5 | 31.2 | 33.3 | 31.2 | 33.3 |
| Somewhat_Agree | 5 | 31.2 | 33.3 | 62.5 | 66.7 |
| Somewhat_Disagree | 5 | 31.2 | 33.3 | 93.8 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 6 | 37.5 | 37.5 | 37.5 | 37.5 |
| Somewhat_Agree | 7 | 43.8 | 43.8 | 81.2 | 81.2 |
| Somewhat_Disagree | 2 | 12.5 | 12.5 | 93.8 | 93.8 |
| Strongly_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 6 | 37.5 | 37.5 | 37.5 | 37.5 |
| Somewhat_Agree | 7 | 43.8 | 43.8 | 81.2 | 81.2 |
| Somewhat_Disagree | 3 | 18.8 | 18.8 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 8 | 50.0 | 50.0 | 50.0 | 50.0 |
| Somewhat_Agree | 7 | 43.8 | 43.8 | 93.8 | 93.8 |
| Somewhat_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 9 | 56.2 | 56.2 | 56.2 | 56.2 |
| Somewhat_Agree | 6 | 37.5 | 37.5 | 93.8 | 93.8 |
| Somewhat_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 10 | 62.5 | 62.5 | 62.5 | 62.5 |
| Somewhat_Agree | 6 | 37.5 | 37.5 | 100.0 | 100.0 |
| Somewhat_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 8 | 50.0 | 50.0 | 50.0 | 50.0 |
| Somewhat_Agree | 6 | 37.5 | 37.5 | 87.5 | 87.5 |
| Somewhat_Disagree | 2 | 12.5 | 12.5 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 8 | 50.0 | 50.0 | 50.0 | 50.0 |
| Somewhat_Agree | 1 | 6.2 | 6.2 | 56.2 | 56.2 |
| Somewhat_Disagree | 7 | 43.8 | 43.8 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 7 | 43.8 | 43.8 | 43.8 | 43.8 |
| Somewhat_Agree | 8 | 50.0 | 50.0 | 93.8 | 93.8 |
| Somewhat_Disagree | 0 | 0.0 | 0.0 | 93.8 | 93.8 |
| Strongly_Disagree | 1 | 6.2 | 6.2 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Strongly_Agree | 8 | 50.0 | 50.0 | 50.0 | 50.0 |
| Somewhat_Agree | 5 | 31.2 | 31.2 | 81.2 | 81.2 |
| Somewhat_Disagree | 3 | 18.8 | 18.8 | 100.0 | 100.0 |
| Strongly_Disagree | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 100.0 | 100.0 |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
# a. Did you live with anyone who was depressed, mentally ill, or suicidal?
d5a <- as.factor(d[,"d5a"])
levels(d5a) <- list(No="1",
Yes="2",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5a <- ordered(d5a, c("No","Yes","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5a)
new.d <- apply_labels(new.d, d5a = "live with depressed")
temp.d <- data.frame (new.d, d5a)
result<-questionr::freq(temp.d$d5a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you live with anyone who was depressed, mentally ill, or suicidal?")
| n | % | val% | |
|---|---|---|---|
| No | 2868 | 80.6 | 82.3 |
| Yes | 323 | 9.1 | 9.3 |
| Dont_know_not_sure | 262 | 7.4 | 7.5 |
| Prefer_not_to_answer | 31 | 0.9 | 0.9 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 72 | 2.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
# b. Did you live with anyone who was a problem drinker or alcoholic?
d5b <- as.factor(d[,"d5b"])
levels(d5b) <- list(No="1",
Yes="2",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5b <- ordered(d5b, c( "No","Yes","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5b)
new.d <- apply_labels(new.d, d5b = "live with alcoholic")
temp.d <- data.frame (new.d, d5b)
result<-questionr::freq(temp.d$d5b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you live with anyone who was a problem drinker or alcoholic?")
| n | % | val% | |
|---|---|---|---|
| No | 2362 | 66.4 | 67.8 |
| Yes | 920 | 25.9 | 26.4 |
| Dont_know_not_sure | 148 | 4.2 | 4.2 |
| Prefer_not_to_answer | 53 | 1.5 | 1.5 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 73 | 2.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
# c. Did you live with anyone who used illegal street drugs or who abused prescription medications?
d5c <- as.factor(d[,"d5c"])
levels(d5c) <- list(No="1",
Yes="2",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5c <- ordered(d5c, c( "No","Yes","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5c)
new.d <- apply_labels(new.d, d5c = "live with illegal street drugs")
temp.d <- data.frame (new.d, d5c)
result<-questionr::freq(temp.d$d5c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. Did you live with anyone who used illegal street drugs or who abused prescription medications?")
| n | % | val% | |
|---|---|---|---|
| No | 2936 | 82.5 | 84.4 |
| Yes | 343 | 9.6 | 9.9 |
| Dont_know_not_sure | 162 | 4.6 | 4.7 |
| Prefer_not_to_answer | 37 | 1.0 | 1.1 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 78 | 2.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
# d. Did you live with anyone who served time or was sentenced to serve time in a prison, jail, or other correctional facility?
d5d <- as.factor(d[,"d5d"])
levels(d5d) <- list(No="1",
Yes="2",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5d <- ordered(d5d, c( "No","Yes","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5d)
new.d <- apply_labels(new.d, d5d = "live with people in a prison")
temp.d <- data.frame (new.d, d5d)
result<-questionr::freq(temp.d$d5d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. Did you live with anyone who served time or was sentenced to serve time in a prison, etc?")
| n | % | val% | |
|---|---|---|---|
| No | 3014 | 84.7 | 86.4 |
| Yes | 382 | 10.7 | 11.0 |
| Dont_know_not_sure | 52 | 1.5 | 1.5 |
| Prefer_not_to_answer | 37 | 1.0 | 1.1 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 70 | 2.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
# e. Were your parents separated or divorced?
d5e <- as.factor(d[,"d5e"])
levels(d5e) <- list(No="1",
Yes="2",
Not_married="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5e <- ordered(d5e, c( "No","Yes","Not_married","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5e)
new.d <- apply_labels(new.d, d5e = "parents divorced")
temp.d <- data.frame (new.d, d5e)
result<-questionr::freq(temp.d$d5e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. Were your parents separated or divorced?")
| n | % | val% | |
|---|---|---|---|
| No | 2101 | 59.1 | 60.4 |
| Yes | 979 | 27.5 | 28.1 |
| Not_married | 286 | 8.0 | 8.2 |
| Dont_know_not_sure | 49 | 1.4 | 1.4 |
| Prefer_not_to_answer | 58 | 1.6 | 1.7 |
| Scantron_Error | 6 | 0.2 | 0.2 |
| NA | 78 | 2.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
# f. How often did your parents or adults in your home ever slap, hit, kick, punch or beat each other up?
d5f <- as.factor(d[,"d5f"])
levels(d5f) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5f <- ordered(d5f, c("Never", "Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5f)
new.d <- apply_labels(new.d, d5f = "violence to each other")
temp.d <- data.frame (new.d, d5f)
result<-questionr::freq(temp.d$d5f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. How often did your parents or adults in your home ever slap, hit, kick, punch or beat each other up?")
| n | % | val% | |
|---|---|---|---|
| Never | 2152 | 60.5 | 62.2 |
| Once | 230 | 6.5 | 6.6 |
| More_than_once | 527 | 14.8 | 15.2 |
| Dont_know_not_sure | 400 | 11.2 | 11.6 |
| Prefer_not_to_answer | 148 | 4.2 | 4.3 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 97 | 2.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
# g. How often did a parent or adult in your home ever hit, beat, kick, or physically hurt you in any way?
d5g <- as.factor(d[,"d5g"])
levels(d5g) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5g <- ordered(d5g, c("Never", "Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5g)
new.d <- apply_labels(new.d, d5g = "violence to you")
temp.d <- data.frame (new.d, d5g)
result<-questionr::freq(temp.d$d5g,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g. How often did a parent or adult in your home ever hit, beat, kick, or physically hurt you in any way?")
| n | % | val% | |
|---|---|---|---|
| Never | 2560 | 72.0 | 74.0 |
| Once | 135 | 3.8 | 3.9 |
| More_than_once | 510 | 14.3 | 14.7 |
| Dont_know_not_sure | 137 | 3.9 | 4.0 |
| Prefer_not_to_answer | 116 | 3.3 | 3.4 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 97 | 2.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
# h. How often did a parent or adult in your home ever swear at you, insult you, or put you down?
d5h <- as.factor(d[,"d5h"])
levels(d5h) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5h <- ordered(d5h, c("Never", "Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5h)
new.d <- apply_labels(new.d, d5h = "swear insult")
temp.d <- data.frame (new.d, d5h)
result<-questionr::freq(temp.d$d5h,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "h. How often did a parent or adult in your home ever swear at you, insult you, or put you down?")
| n | % | val% | |
|---|---|---|---|
| Never | 2077 | 58.4 | 60.0 |
| Once | 158 | 4.4 | 4.6 |
| More_than_once | 864 | 24.3 | 25.0 |
| Dont_know_not_sure | 252 | 7.1 | 7.3 |
| Prefer_not_to_answer | 110 | 3.1 | 3.2 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 95 | 2.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
# i. How often did anyone at least 5 years older than you or an adult, ever touch you sexually?
d5i <- as.factor(d[,"d5i"])
levels(d5i) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5i <- ordered(d5i, c("Never", "Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5i)
new.d <- apply_labels(new.d, d5i = "touch you sexually")
temp.d <- data.frame (new.d, d5i)
result<-questionr::freq(temp.d$d5i,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "i. How often did anyone at least 5 years older than you or an adult, ever touch you sexually?")
| n | % | val% | |
|---|---|---|---|
| Never | 3121 | 87.7 | 89.7 |
| Once | 150 | 4.2 | 4.3 |
| More_than_once | 113 | 3.2 | 3.2 |
| Dont_know_not_sure | 52 | 1.5 | 1.5 |
| Prefer_not_to_answer | 43 | 1.2 | 1.2 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 77 | 2.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
# j. How often did anyone at least 5 years older than you or an adult, try to make you touch them sexually?
d5j <- as.factor(d[,"d5j"])
levels(d5j) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5j <- ordered(d5j, c("Never","Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5j)
new.d <- apply_labels(new.d, d5j = "touch them sexually")
temp.d <- data.frame (new.d, d5j)
result<-questionr::freq(temp.d$d5j,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "j. How often did anyone at least 5 years older than you or an adult, try to make you touch them sexually?")
| n | % | val% | |
|---|---|---|---|
| Never | 3181 | 89.4 | 91.4 |
| Once | 121 | 3.4 | 3.5 |
| More_than_once | 92 | 2.6 | 2.6 |
| Dont_know_not_sure | 39 | 1.1 | 1.1 |
| Prefer_not_to_answer | 45 | 1.3 | 1.3 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 78 | 2.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
# k. How often did anyone at least 5 years older than you or an adult, force you to have sex?
d5k <- as.factor(d[,"d5k"])
levels(d5k) <- list(Never="1",
Once="2",
More_than_once="3",
Dont_know_not_sure="88",
Prefer_not_to_answer="99",
Scantron_Error="*")
d5k <- ordered(d5k, c("Never","Once","More_than_once","Dont_know_not_sure","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, d5k)
new.d <- apply_labels(new.d, d5k = "forced to have sex")
temp.d <- data.frame (new.d, d5k)
result<-questionr::freq(temp.d$d5k,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "k. How often did anyone at least 5 years older than you or an adult, force you to have sex?")
| n | % | val% | |
|---|---|---|---|
| Never | 3302 | 92.8 | 94.9 |
| Once | 56 | 1.6 | 1.6 |
| More_than_once | 53 | 1.5 | 1.5 |
| Dont_know_not_sure | 30 | 0.8 | 0.9 |
| Prefer_not_to_answer | 40 | 1.1 | 1.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 76 | 2.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 266 | 82.9 | 83.4 |
| Yes | 26 | 8.1 | 8.2 |
| Dont_know_not_sure | 25 | 7.8 | 7.8 |
| Prefer_not_to_answer | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 218 | 67.9 | 68.3 |
| Yes | 89 | 27.7 | 27.9 |
| Dont_know_not_sure | 9 | 2.8 | 2.8 |
| Prefer_not_to_answer | 3 | 0.9 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 263 | 81.9 | 82.4 |
| Yes | 43 | 13.4 | 13.5 |
| Dont_know_not_sure | 9 | 2.8 | 2.8 |
| Prefer_not_to_answer | 4 | 1.2 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 265 | 82.6 | 83.1 |
| Yes | 46 | 14.3 | 14.4 |
| Dont_know_not_sure | 4 | 1.2 | 1.3 |
| Prefer_not_to_answer | 4 | 1.2 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 163 | 50.8 | 51.6 |
| Yes | 130 | 40.5 | 41.1 |
| Not_married | 9 | 2.8 | 2.8 |
| Dont_know_not_sure | 10 | 3.1 | 3.2 |
| Prefer_not_to_answer | 4 | 1.2 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 176 | 54.8 | 55.7 |
| Once | 26 | 8.1 | 8.2 |
| More_than_once | 65 | 20.2 | 20.6 |
| Dont_know_not_sure | 35 | 10.9 | 11.1 |
| Prefer_not_to_answer | 13 | 4.0 | 4.1 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 229 | 71.3 | 72.5 |
| Once | 13 | 4.0 | 4.1 |
| More_than_once | 53 | 16.5 | 16.8 |
| Dont_know_not_sure | 10 | 3.1 | 3.2 |
| Prefer_not_to_answer | 11 | 3.4 | 3.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 181 | 56.4 | 58.2 |
| Once | 16 | 5.0 | 5.1 |
| More_than_once | 89 | 27.7 | 28.6 |
| Dont_know_not_sure | 18 | 5.6 | 5.8 |
| Prefer_not_to_answer | 6 | 1.9 | 1.9 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 10 | 3.1 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 274 | 85.4 | 86.4 |
| Once | 18 | 5.6 | 5.7 |
| More_than_once | 12 | 3.7 | 3.8 |
| Dont_know_not_sure | 8 | 2.5 | 2.5 |
| Prefer_not_to_answer | 5 | 1.6 | 1.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 284 | 88.5 | 89.9 |
| Once | 15 | 4.7 | 4.7 |
| More_than_once | 8 | 2.5 | 2.5 |
| Dont_know_not_sure | 4 | 1.2 | 1.3 |
| Prefer_not_to_answer | 5 | 1.6 | 1.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 296 | 92.2 | 93.7 |
| Once | 10 | 3.1 | 3.2 |
| More_than_once | 4 | 1.2 | 1.3 |
| Dont_know_not_sure | 3 | 0.9 | 0.9 |
| Prefer_not_to_answer | 3 | 0.9 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 170 | 81.0 | 81.0 |
| Yes | 21 | 10.0 | 10.0 |
| Dont_know_not_sure | 17 | 8.1 | 8.1 |
| Prefer_not_to_answer | 2 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 140 | 66.7 | 67.0 |
| Yes | 55 | 26.2 | 26.3 |
| Dont_know_not_sure | 9 | 4.3 | 4.3 |
| Prefer_not_to_answer | 5 | 2.4 | 2.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 166 | 79.0 | 79.4 |
| Yes | 32 | 15.2 | 15.3 |
| Dont_know_not_sure | 8 | 3.8 | 3.8 |
| Prefer_not_to_answer | 3 | 1.4 | 1.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 176 | 83.8 | 84.2 |
| Yes | 28 | 13.3 | 13.4 |
| Dont_know_not_sure | 4 | 1.9 | 1.9 |
| Prefer_not_to_answer | 1 | 0.5 | 0.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 109 | 51.9 | 52.2 |
| Yes | 75 | 35.7 | 35.9 |
| Not_married | 20 | 9.5 | 9.6 |
| Dont_know_not_sure | 1 | 0.5 | 0.5 |
| Prefer_not_to_answer | 4 | 1.9 | 1.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 128 | 61.0 | 61.2 |
| Once | 18 | 8.6 | 8.6 |
| More_than_once | 33 | 15.7 | 15.8 |
| Dont_know_not_sure | 19 | 9.0 | 9.1 |
| Prefer_not_to_answer | 11 | 5.2 | 5.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 152 | 72.4 | 73.1 |
| Once | 9 | 4.3 | 4.3 |
| More_than_once | 35 | 16.7 | 16.8 |
| Dont_know_not_sure | 3 | 1.4 | 1.4 |
| Prefer_not_to_answer | 9 | 4.3 | 4.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 2 | 1.0 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 113 | 53.8 | 54.1 |
| Once | 14 | 6.7 | 6.7 |
| More_than_once | 60 | 28.6 | 28.7 |
| Dont_know_not_sure | 12 | 5.7 | 5.7 |
| Prefer_not_to_answer | 10 | 4.8 | 4.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 183 | 87.1 | 87.6 |
| Once | 13 | 6.2 | 6.2 |
| More_than_once | 8 | 3.8 | 3.8 |
| Dont_know_not_sure | 4 | 1.9 | 1.9 |
| Prefer_not_to_answer | 1 | 0.5 | 0.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 189 | 90.0 | 90.9 |
| Once | 8 | 3.8 | 3.8 |
| More_than_once | 8 | 3.8 | 3.8 |
| Dont_know_not_sure | 1 | 0.5 | 0.5 |
| Prefer_not_to_answer | 1 | 0.5 | 0.5 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 2 | 1.0 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 197 | 93.8 | 94.3 |
| Once | 3 | 1.4 | 1.4 |
| More_than_once | 3 | 1.4 | 1.4 |
| Dont_know_not_sure | 4 | 1.9 | 1.9 |
| Prefer_not_to_answer | 2 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 241 | 76.5 | 79.8 |
| Yes | 33 | 10.5 | 10.9 |
| Dont_know_not_sure | 25 | 7.9 | 8.3 |
| Prefer_not_to_answer | 2 | 0.6 | 0.7 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 199 | 63.2 | 65.9 |
| Yes | 86 | 27.3 | 28.5 |
| Dont_know_not_sure | 16 | 5.1 | 5.3 |
| Prefer_not_to_answer | 1 | 0.3 | 0.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 4.1 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 251 | 79.7 | 82.8 |
| Yes | 40 | 12.7 | 13.2 |
| Dont_know_not_sure | 11 | 3.5 | 3.6 |
| Prefer_not_to_answer | 1 | 0.3 | 0.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 259 | 82.2 | 85.5 |
| Yes | 38 | 12.1 | 12.5 |
| Dont_know_not_sure | 3 | 1.0 | 1.0 |
| Prefer_not_to_answer | 2 | 0.6 | 0.7 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 168 | 53.3 | 55.4 |
| Yes | 104 | 33.0 | 34.3 |
| Not_married | 21 | 6.7 | 6.9 |
| Dont_know_not_sure | 3 | 1.0 | 1.0 |
| Prefer_not_to_answer | 6 | 1.9 | 2.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 170 | 54.0 | 56.1 |
| Once | 28 | 8.9 | 9.2 |
| More_than_once | 64 | 20.3 | 21.1 |
| Dont_know_not_sure | 29 | 9.2 | 9.6 |
| Prefer_not_to_answer | 11 | 3.5 | 3.6 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 207 | 65.7 | 68.3 |
| Once | 13 | 4.1 | 4.3 |
| More_than_once | 65 | 20.6 | 21.5 |
| Dont_know_not_sure | 11 | 3.5 | 3.6 |
| Prefer_not_to_answer | 6 | 1.9 | 2.0 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 153 | 48.6 | 50.3 |
| Once | 21 | 6.7 | 6.9 |
| More_than_once | 97 | 30.8 | 31.9 |
| Dont_know_not_sure | 24 | 7.6 | 7.9 |
| Prefer_not_to_answer | 9 | 2.9 | 3.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 269 | 85.4 | 88.5 |
| Once | 15 | 4.8 | 4.9 |
| More_than_once | 12 | 3.8 | 3.9 |
| Dont_know_not_sure | 5 | 1.6 | 1.6 |
| Prefer_not_to_answer | 3 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 280 | 88.9 | 91.5 |
| Once | 11 | 3.5 | 3.6 |
| More_than_once | 10 | 3.2 | 3.3 |
| Dont_know_not_sure | 3 | 1.0 | 1.0 |
| Prefer_not_to_answer | 2 | 0.6 | 0.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 294 | 93.3 | 96.1 |
| Once | 6 | 1.9 | 2.0 |
| More_than_once | 3 | 1.0 | 1.0 |
| Dont_know_not_sure | 2 | 0.6 | 0.7 |
| Prefer_not_to_answer | 1 | 0.3 | 0.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.9 | NA |
| Total | 315 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 268 | 75.3 | 76.6 |
| Yes | 44 | 12.4 | 12.6 |
| Dont_know_not_sure | 35 | 9.8 | 10.0 |
| Prefer_not_to_answer | 3 | 0.8 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.7 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 206 | 57.9 | 58.9 |
| Yes | 122 | 34.3 | 34.9 |
| Dont_know_not_sure | 19 | 5.3 | 5.4 |
| Prefer_not_to_answer | 3 | 0.8 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.7 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 269 | 75.6 | 77.3 |
| Yes | 55 | 15.4 | 15.8 |
| Dont_know_not_sure | 22 | 6.2 | 6.3 |
| Prefer_not_to_answer | 2 | 0.6 | 0.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 2.2 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 295 | 82.9 | 84.3 |
| Yes | 45 | 12.6 | 12.9 |
| Dont_know_not_sure | 6 | 1.7 | 1.7 |
| Prefer_not_to_answer | 4 | 1.1 | 1.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.7 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 204 | 57.3 | 58.8 |
| Yes | 103 | 28.9 | 29.7 |
| Not_married | 27 | 7.6 | 7.8 |
| Dont_know_not_sure | 4 | 1.1 | 1.2 |
| Prefer_not_to_answer | 8 | 2.2 | 2.3 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 9 | 2.5 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 214 | 60.1 | 62.6 |
| Once | 20 | 5.6 | 5.8 |
| More_than_once | 42 | 11.8 | 12.3 |
| Dont_know_not_sure | 45 | 12.6 | 13.2 |
| Prefer_not_to_answer | 21 | 5.9 | 6.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 3.9 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 252 | 70.8 | 72.8 |
| Once | 15 | 4.2 | 4.3 |
| More_than_once | 50 | 14.0 | 14.5 |
| Dont_know_not_sure | 15 | 4.2 | 4.3 |
| Prefer_not_to_answer | 14 | 3.9 | 4.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 187 | 52.5 | 54.4 |
| Once | 16 | 4.5 | 4.7 |
| More_than_once | 104 | 29.2 | 30.2 |
| Dont_know_not_sure | 27 | 7.6 | 7.8 |
| Prefer_not_to_answer | 10 | 2.8 | 2.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.4 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 305 | 85.7 | 88.4 |
| Once | 14 | 3.9 | 4.1 |
| More_than_once | 12 | 3.4 | 3.5 |
| Dont_know_not_sure | 7 | 2.0 | 2.0 |
| Prefer_not_to_answer | 7 | 2.0 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 317 | 89.0 | 91.9 |
| Once | 7 | 2.0 | 2.0 |
| More_than_once | 11 | 3.1 | 3.2 |
| Dont_know_not_sure | 3 | 0.8 | 0.9 |
| Prefer_not_to_answer | 7 | 2.0 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.1 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 323 | 90.7 | 93.4 |
| Once | 7 | 2.0 | 2.0 |
| More_than_once | 5 | 1.4 | 1.4 |
| Dont_know_not_sure | 4 | 1.1 | 1.2 |
| Prefer_not_to_answer | 7 | 2.0 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 462 | 79.0 | 80.9 |
| Yes | 60 | 10.3 | 10.5 |
| Dont_know_not_sure | 43 | 7.4 | 7.5 |
| Prefer_not_to_answer | 6 | 1.0 | 1.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 2.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 424 | 72.5 | 74.6 |
| Yes | 109 | 18.6 | 19.2 |
| Dont_know_not_sure | 27 | 4.6 | 4.8 |
| Prefer_not_to_answer | 7 | 1.2 | 1.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 17 | 2.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 474 | 81.0 | 83.5 |
| Yes | 49 | 8.4 | 8.6 |
| Dont_know_not_sure | 35 | 6.0 | 6.2 |
| Prefer_not_to_answer | 9 | 1.5 | 1.6 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 17 | 2.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 494 | 84.4 | 86.7 |
| Yes | 59 | 10.1 | 10.4 |
| Dont_know_not_sure | 8 | 1.4 | 1.4 |
| Prefer_not_to_answer | 8 | 1.4 | 1.4 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 15 | 2.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 365 | 62.4 | 63.6 |
| Yes | 147 | 25.1 | 25.6 |
| Not_married | 48 | 8.2 | 8.4 |
| Dont_know_not_sure | 7 | 1.2 | 1.2 |
| Prefer_not_to_answer | 7 | 1.2 | 1.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 1.9 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 383 | 65.5 | 67.7 |
| Once | 28 | 4.8 | 4.9 |
| More_than_once | 70 | 12.0 | 12.4 |
| Dont_know_not_sure | 66 | 11.3 | 11.7 |
| Prefer_not_to_answer | 19 | 3.2 | 3.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 19 | 3.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 433 | 74.0 | 76.0 |
| Once | 17 | 2.9 | 3.0 |
| More_than_once | 71 | 12.1 | 12.5 |
| Dont_know_not_sure | 29 | 5.0 | 5.1 |
| Prefer_not_to_answer | 20 | 3.4 | 3.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 2.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 388 | 66.3 | 67.8 |
| Once | 15 | 2.6 | 2.6 |
| More_than_once | 114 | 19.5 | 19.9 |
| Dont_know_not_sure | 43 | 7.4 | 7.5 |
| Prefer_not_to_answer | 12 | 2.1 | 2.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 13 | 2.2 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 535 | 91.5 | 93.9 |
| Once | 11 | 1.9 | 1.9 |
| More_than_once | 14 | 2.4 | 2.5 |
| Dont_know_not_sure | 4 | 0.7 | 0.7 |
| Prefer_not_to_answer | 6 | 1.0 | 1.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 2.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 536 | 91.6 | 93.9 |
| Once | 12 | 2.1 | 2.1 |
| More_than_once | 10 | 1.7 | 1.8 |
| Dont_know_not_sure | 5 | 0.9 | 0.9 |
| Prefer_not_to_answer | 8 | 1.4 | 1.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 2.4 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 544 | 93.0 | 95.4 |
| Once | 5 | 0.9 | 0.9 |
| More_than_once | 10 | 1.7 | 1.8 |
| Dont_know_not_sure | 4 | 0.7 | 0.7 |
| Prefer_not_to_answer | 7 | 1.2 | 1.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 2.6 | NA |
| Total | 585 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1448 | 82.6 | 84.3 |
| Yes | 137 | 7.8 | 8.0 |
| Dont_know_not_sure | 116 | 6.6 | 6.8 |
| Prefer_not_to_answer | 16 | 0.9 | 0.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 37 | 2.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1165 | 66.4 | 67.7 |
| Yes | 453 | 25.8 | 26.3 |
| Dont_know_not_sure | 68 | 3.9 | 4.0 |
| Prefer_not_to_answer | 34 | 1.9 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 34 | 1.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1500 | 85.5 | 87.4 |
| Yes | 121 | 6.9 | 7.1 |
| Dont_know_not_sure | 77 | 4.4 | 4.5 |
| Prefer_not_to_answer | 18 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 38 | 2.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1511 | 86.1 | 87.8 |
| Yes | 165 | 9.4 | 9.6 |
| Dont_know_not_sure | 26 | 1.5 | 1.5 |
| Prefer_not_to_answer | 18 | 1.0 | 1.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 34 | 1.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 1082 | 61.7 | 63.1 |
| Yes | 418 | 23.8 | 24.4 |
| Not_married | 158 | 9.0 | 9.2 |
| Dont_know_not_sure | 24 | 1.4 | 1.4 |
| Prefer_not_to_answer | 29 | 1.7 | 1.7 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 39 | 2.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1071 | 61.1 | 62.7 |
| Once | 108 | 6.2 | 6.3 |
| More_than_once | 251 | 14.3 | 14.7 |
| Dont_know_not_sure | 204 | 11.6 | 11.9 |
| Prefer_not_to_answer | 73 | 4.2 | 4.3 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 46 | 2.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1279 | 72.9 | 75.2 |
| Once | 68 | 3.9 | 4.0 |
| More_than_once | 231 | 13.2 | 13.6 |
| Dont_know_not_sure | 67 | 3.8 | 3.9 |
| Prefer_not_to_answer | 55 | 3.1 | 3.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 53 | 3.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1049 | 59.8 | 61.5 |
| Once | 75 | 4.3 | 4.4 |
| More_than_once | 394 | 22.5 | 23.1 |
| Dont_know_not_sure | 125 | 7.1 | 7.3 |
| Prefer_not_to_answer | 63 | 3.6 | 3.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 48 | 2.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1543 | 88.0 | 89.8 |
| Once | 79 | 4.5 | 4.6 |
| More_than_once | 54 | 3.1 | 3.1 |
| Dont_know_not_sure | 21 | 1.2 | 1.2 |
| Prefer_not_to_answer | 21 | 1.2 | 1.2 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 35 | 2.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1563 | 89.1 | 91.0 |
| Once | 68 | 3.9 | 4.0 |
| More_than_once | 43 | 2.5 | 2.5 |
| Dont_know_not_sure | 21 | 1.2 | 1.2 |
| Prefer_not_to_answer | 22 | 1.3 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 37 | 2.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 1635 | 93.2 | 95.2 |
| Once | 25 | 1.4 | 1.5 |
| More_than_once | 27 | 1.5 | 1.6 |
| Dont_know_not_sure | 11 | 0.6 | 0.6 |
| Prefer_not_to_answer | 20 | 1.1 | 1.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 36 | 2.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 81.2 |
| Yes | 2 | 12.5 | 12.5 |
| Dont_know_not_sure | 1 | 6.2 | 6.2 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 10 | 62.5 | 62.5 |
| Yes | 6 | 37.5 | 37.5 |
| Dont_know_not_sure | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 13 | 81.2 | 81.2 |
| Yes | 3 | 18.8 | 18.8 |
| Dont_know_not_sure | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 14 | 87.5 | 87.5 |
| Yes | 1 | 6.2 | 6.2 |
| Dont_know_not_sure | 1 | 6.2 | 6.2 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| No | 10 | 62.5 | 66.7 |
| Yes | 2 | 12.5 | 13.3 |
| Not_married | 3 | 18.8 | 20.0 |
| Dont_know_not_sure | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 10 | 62.5 | 62.5 |
| Once | 2 | 12.5 | 12.5 |
| More_than_once | 2 | 12.5 | 12.5 |
| Dont_know_not_sure | 2 | 12.5 | 12.5 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 8 | 50.0 | 50.0 |
| Once | 0 | 0.0 | 0.0 |
| More_than_once | 5 | 31.2 | 31.2 |
| Dont_know_not_sure | 2 | 12.5 | 12.5 |
| Prefer_not_to_answer | 1 | 6.2 | 6.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 6 | 37.5 | 37.5 |
| Once | 1 | 6.2 | 6.2 |
| More_than_once | 6 | 37.5 | 37.5 |
| Dont_know_not_sure | 3 | 18.8 | 18.8 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 12 | 75.0 | 75.0 |
| Once | 0 | 0.0 | 0.0 |
| More_than_once | 1 | 6.2 | 6.2 |
| Dont_know_not_sure | 3 | 18.8 | 18.8 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 12 | 75.0 | 75.0 |
| Once | 0 | 0.0 | 0.0 |
| More_than_once | 2 | 12.5 | 12.5 |
| Dont_know_not_sure | 2 | 12.5 | 12.5 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
| n | % | val% | |
|---|---|---|---|
| Never | 13 | 81.2 | 81.2 |
| Once | 0 | 0.0 | 0.0 |
| More_than_once | 1 | 6.2 | 6.2 |
| Dont_know_not_sure | 2 | 12.5 | 12.5 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
# 1
e1_1 <- as.factor(d[,"e1_1"])
levels(e1_1) <- list(High_PSA_test="1",
Scantron_Error="*")
e1_1 <- ordered(e1_1, c("High_PSA_test","Scantron_Error"))
new.d <- data.frame(new.d, e1_1)
new.d <- apply_labels(new.d, e1_1 = "High_PSA_test")
temp.d <- data.frame (new.d, e1_1)
result<-questionr::freq(temp.d$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 2771 | 77.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 786 | 22.1 | NA |
| Total | 3557 | 100.0 | 100 |
#2
e1_2 <- as.factor(d[,"e1_2"])
levels(e1_2) <- list(Digital_rectal_exam="1",
Scantron_Error="*")
e1_2 <- ordered(e1_2, c("Digital_rectal_exam","Scantron_Error"))
new.d <- data.frame(new.d, e1_2)
new.d <- apply_labels(new.d, e1_2 = "digital rectal exam")
temp.d <- data.frame (new.d, e1_2)
result<-questionr::freq(temp.d$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 940 | 26.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2617 | 73.6 | NA |
| Total | 3557 | 100.0 | 100 |
#3
e1_3 <- as.factor(d[,"e1_3"])
levels(e1_3) <- list(Digital_rectal_exam="1",
Scantron_Error="*")
e1_3 <- ordered(e1_3, c("Digital_rectal_exam","Scantron_Error"))
new.d <- data.frame(new.d, e1_3)
new.d <- apply_labels(new.d, e1_3 = "urinary sexual or bowel problems")
temp.d <- data.frame (new.d, e1_3)
result<-questionr::freq(temp.d$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 658 | 18.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2899 | 81.5 | NA |
| Total | 3557 | 100.0 | 100 |
#4
e1_4 <- as.factor(d[,"e1_4"])
levels(e1_4) <- list(Digital_rectal_exam="1",
Scantron_Error="*")
e1_4 <- ordered(e1_4, c("Digital_rectal_exam","Scantron_Error"))
new.d <- data.frame(new.d, e1_4)
new.d <- apply_labels(new.d, e1_4 = "bone pain")
temp.d <- data.frame (new.d, e1_4)
result<-questionr::freq(temp.d$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 68 | 1.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3489 | 98.1 | NA |
| Total | 3557 | 100.0 | 100 |
#5
e1_5 <- as.factor(d[,"e1_5"])
levels(e1_5) <- list(Digital_rectal_exam="1",
Scantron_Error="*")
e1_5 <- ordered(e1_5, c("Digital_rectal_exam","Scantron_Error"))
new.d <- data.frame(new.d, e1_5)
new.d <- apply_labels(new.d, e1_5 = "fearful")
temp.d <- data.frame (new.d, e1_5)
result<-questionr::freq(temp.d$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 147 | 4.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3410 | 95.9 | NA |
| Total | 3557 | 100.0 | 100 |
#6
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 256 | 79.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 65 | 20.2 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 74 | 23.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 247 | 76.9 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 75 | 23.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 246 | 76.6 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 5 | 1.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 316 | 98.4 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 5 | 1.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 316 | 98.4 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 172 | 81.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 38 | 18.1 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 45 | 21.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 165 | 78.6 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 40 | 19 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 170 | 81 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 2 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 208 | 99 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 6 | 2.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 204 | 97.1 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 235 | 74.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 80 | 25.4 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 84 | 26.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 231 | 73.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 57 | 18.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 258 | 81.9 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 7 | 2.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 308 | 97.8 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 16 | 5.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 299 | 94.9 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 260 | 73 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 96 | 27 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 112 | 31.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 244 | 68.5 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 59 | 16.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 297 | 83.4 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 7 | 2 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 349 | 98 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 27 | 7.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 329 | 92.4 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 447 | 76.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 138 | 23.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 157 | 26.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 428 | 73.2 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 112 | 19.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 473 | 80.9 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 14 | 2.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 571 | 97.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 13 | 2.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 572 | 97.8 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 1390 | 79.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 364 | 20.8 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 463 | 26.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1291 | 73.6 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 311 | 17.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1443 | 82.3 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 31 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1723 | 98.2 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 79 | 4.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1675 | 95.5 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e1_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. I had a high PSA (‘prostate specific antigen’) test")
| n | % | val% | |
|---|---|---|---|
| High_PSA_test | 11 | 68.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 5 | 31.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. My doctor did a digital rectal exam that indicated an abnormality")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 5 | 31.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. I had urinary, sexual, or bowel problems that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 4 | 25 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 12 | 75 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e1_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. I had bone pain that I went to see my doctor about")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 2 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 87.5 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e1_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. I was fearful I had cancer")
| n | % | val% | |
|---|---|---|---|
| Digital_rectal_exam | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e2aa <- as.factor(d[,"e2aa"])
levels(e2aa) <- list(No="1",
Yes="2",
Scantron_Error="*")
e2aa <- ordered(e2aa, c("Yes","No","Scantron_Error"))
new.d <- data.frame(new.d, e2aa)
new.d <- apply_labels(new.d, e2aa = "biopsies negative")
temp.d <- data.frame (new.d, e2aa)
result<-questionr::freq(temp.d$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 459 | 12.9 | 15.1 |
| No | 2581 | 72.6 | 84.8 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 514 | 14.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
e2ab <- as.factor(d[,"e2ab"])
levels(e2ab) <- list(One="1",
Two="2",
Three_more="3",
Scantron_Error="*")
e2ab <- ordered(e2ab, c("One","Two","Three_more","Scantron_Error"))
new.d <- data.frame(new.d, e2ab)
new.d <- apply_labels(new.d, e2ab = "biopsies negative-number")
temp.d <- data.frame (new.d, e2ab)
result<-questionr::freq(temp.d$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 253 | 7.1 | 48.2 | 7.1 | 48.2 |
| Two | 148 | 4.2 | 28.2 | 11.3 | 76.4 |
| Three_more | 124 | 3.5 | 23.6 | 14.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 14.8 | 100.0 |
| NA | 3032 | 85.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
e2ba <- as.factor(d[,"e2ba"])
levels(e2ba) <- list(No="1",
Yes="2",
Scantron_Error="*")
e2ba <- ordered(e2ba, c("Yes","No","Scantron_Error"))
new.d <- data.frame(new.d, e2ba)
new.d <- apply_labels(new.d, e2ba = "Normal PSA blood tests")
temp.d <- data.frame (new.d, e2ba)
result<-questionr::freq(temp.d$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 1555 | 43.7 | 63.8 |
| No | 864 | 24.3 | 35.5 |
| Scantron_Error | 17 | 0.5 | 0.7 |
| NA | 1121 | 31.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
e2bb <- as.factor(d[,"e2bb"])
levels(e2bb) <- list(One="1",
Two="2",
Three_more="3",
Scantron_Error="*")
e2bb <- ordered(e2bb, c("One","Two","Three_more","Scantron_Error"))
new.d <- data.frame(new.d, e2bb)
new.d <- apply_labels(new.d, e2bb = "Normal PSA blood tests-number")
temp.d <- data.frame (new.d, e2bb)
result<-questionr::freq(temp.d$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 170 | 4.8 | 23.9 | 4.8 | 23.9 |
| Two | 268 | 7.5 | 37.7 | 12.3 | 61.6 |
| Three_more | 272 | 7.6 | 38.3 | 20.0 | 99.9 |
| Scantron_Error | 1 | 0.0 | 0.1 | 20.0 | 100.0 |
| NA | 2846 | 80.0 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 44 | 13.7 | 14.8 |
| No | 254 | 79.1 | 85.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 23 | 7.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 24 | 7.5 | 49.0 | 7.5 | 49.0 |
| Two | 11 | 3.4 | 22.4 | 10.9 | 71.4 |
| Three_more | 14 | 4.4 | 28.6 | 15.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 15.3 | 100.0 |
| NA | 272 | 84.7 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 177 | 55.1 | 71.1 |
| No | 69 | 21.5 | 27.7 |
| Scantron_Error | 3 | 0.9 | 1.2 |
| NA | 72 | 22.4 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 13 | 4.0 | 21.7 | 4.0 | 21.7 |
| Two | 19 | 5.9 | 31.7 | 10.0 | 53.3 |
| Three_more | 28 | 8.7 | 46.7 | 18.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 18.7 | 100.0 |
| NA | 261 | 81.3 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 30 | 14.3 | 15.9 |
| No | 159 | 75.7 | 84.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 10.0 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 17 | 8.1 | 53.1 | 8.1 | 53.1 |
| Two | 9 | 4.3 | 28.1 | 12.4 | 81.2 |
| Three_more | 6 | 2.9 | 18.8 | 15.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 15.2 | 100.0 |
| NA | 178 | 84.8 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 105 | 50.0 | 70 |
| No | 45 | 21.4 | 30 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 60 | 28.6 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 13 | 6.2 | 28.3 | 6.2 | 28.3 |
| Two | 20 | 9.5 | 43.5 | 15.7 | 71.7 |
| Three_more | 13 | 6.2 | 28.3 | 21.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 21.9 | 100.0 |
| NA | 164 | 78.1 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 45 | 14.3 | 16.5 |
| No | 228 | 72.4 | 83.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 42 | 13.3 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 21 | 6.7 | 43.8 | 6.7 | 43.8 |
| Two | 17 | 5.4 | 35.4 | 12.1 | 79.2 |
| Three_more | 10 | 3.2 | 20.8 | 15.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 15.2 | 100.0 |
| NA | 267 | 84.8 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 133 | 42.2 | 58.1 |
| No | 96 | 30.5 | 41.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 86 | 27.3 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 20 | 6.3 | 31.7 | 6.3 | 31.7 |
| Two | 18 | 5.7 | 28.6 | 12.1 | 60.3 |
| Three_more | 25 | 7.9 | 39.7 | 20.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 20.0 | 100.0 |
| NA | 252 | 80.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 42 | 11.8 | 13.8 |
| No | 263 | 73.9 | 86.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 51 | 14.3 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 23 | 6.5 | 43.4 | 6.5 | 43.4 |
| Two | 18 | 5.1 | 34.0 | 11.5 | 77.4 |
| Three_more | 12 | 3.4 | 22.6 | 14.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 14.9 | 100.0 |
| NA | 303 | 85.1 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 141 | 39.6 | 59.2 |
| No | 93 | 26.1 | 39.1 |
| Scantron_Error | 4 | 1.1 | 1.7 |
| NA | 118 | 33.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 19 | 5.3 | 24.1 | 5.3 | 24.1 |
| Two | 30 | 8.4 | 38.0 | 13.8 | 62.0 |
| Three_more | 30 | 8.4 | 38.0 | 22.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 22.2 | 100.0 |
| NA | 277 | 77.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 60 | 10.3 | 12.6 |
| No | 416 | 71.1 | 87.0 |
| Scantron_Error | 2 | 0.3 | 0.4 |
| NA | 107 | 18.3 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 35 | 6.0 | 40.7 | 6.0 | 40.7 |
| Two | 25 | 4.3 | 29.1 | 10.3 | 69.8 |
| Three_more | 26 | 4.4 | 30.2 | 14.7 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 14.7 | 100.0 |
| NA | 499 | 85.3 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 233 | 39.8 | 59.1 |
| No | 159 | 27.2 | 40.4 |
| Scantron_Error | 2 | 0.3 | 0.5 |
| NA | 191 | 32.6 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 33 | 5.6 | 29.5 | 5.6 | 29.5 |
| Two | 35 | 6.0 | 31.2 | 11.6 | 60.7 |
| Three_more | 44 | 7.5 | 39.3 | 19.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 19.1 | 100.0 |
| NA | 473 | 80.9 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 235 | 13.4 | 15.8 |
| No | 1249 | 71.2 | 84.1 |
| Scantron_Error | 1 | 0.1 | 0.1 |
| NA | 269 | 15.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 130 | 7.4 | 51.4 | 7.4 | 51.4 |
| Two | 67 | 3.8 | 26.5 | 11.2 | 77.9 |
| Three_more | 56 | 3.2 | 22.1 | 14.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 14.4 | 100.0 |
| NA | 1501 | 85.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 757 | 43.2 | 65.1 |
| No | 398 | 22.7 | 34.2 |
| Scantron_Error | 8 | 0.5 | 0.7 |
| NA | 591 | 33.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 71 | 4.0 | 20.3 | 4.0 | 20.3 |
| Two | 145 | 8.3 | 41.5 | 12.3 | 61.9 |
| Three_more | 132 | 7.5 | 37.8 | 19.8 | 99.7 |
| Scantron_Error | 1 | 0.1 | 0.3 | 19.9 | 100.0 |
| NA | 1405 | 80.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e2aa,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. Did you have any previous prostate biopsies that were negative?")
| n | % | val% | |
|---|---|---|---|
| Yes | 3 | 18.8 | 20 |
| No | 12 | 75.0 | 80 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e2ab,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 3 | 18.8 | 75 | 18.8 | 75 |
| Two | 1 | 6.2 | 25 | 25.0 | 100 |
| Three_more | 0 | 0.0 | 0 | 25.0 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 25.0 | 100 |
| NA | 12 | 75.0 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e2ba,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. Did you have any previous PSA blood tests that were considered normal?")
| n | % | val% | |
|---|---|---|---|
| Yes | 9 | 56.2 | 69.2 |
| No | 4 | 25.0 | 30.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 18.8 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e2bb,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. If yes, How many?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One | 1 | 6.2 | 50 | 6.2 | 50 |
| Two | 1 | 6.2 | 50 | 12.5 | 100 |
| Three_more | 0 | 0.0 | 0 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 12.5 | 100 |
| NA | 14 | 87.5 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
rm(temp.dd)
e3 <- as.factor(d[,"e3"])
levels(e3) <- list(Alone="1",
With_family_or_friends="2",
With_family_and_doctor="3",
With_doctor="4",
Doctor_made="5",
Dont_know_or_remember="88",
Scantron_Error="*")
e3 <- ordered(e3, c("Alone","With_family_or_friends","With_family_and_doctor","With_doctor","Doctor_made","Dont_know_or_remember","Scantron_Error"))
new.d <- data.frame(new.d, e3)
new.d <- apply_labels(new.d, e3 = "decision to have the PSA blood test")
temp.d <- data.frame (new.d, e3)
result<-questionr::freq(temp.d$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 521 | 14.6 | 15.0 |
| With_family_or_friends | 230 | 6.5 | 6.6 |
| With_family_and_doctor | 494 | 13.9 | 14.2 |
| With_doctor | 878 | 24.7 | 25.3 |
| Doctor_made | 1073 | 30.2 | 30.9 |
| Dont_know_or_remember | 204 | 5.7 | 5.9 |
| Scantron_Error | 75 | 2.1 | 2.2 |
| NA | 82 | 2.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 68 | 21.2 | 21.3 |
| With_family_or_friends | 13 | 4.0 | 4.1 |
| With_family_and_doctor | 34 | 10.6 | 10.7 |
| With_doctor | 85 | 26.5 | 26.6 |
| Doctor_made | 105 | 32.7 | 32.9 |
| Dont_know_or_remember | 12 | 3.7 | 3.8 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 34 | 16.2 | 16.5 |
| With_family_or_friends | 13 | 6.2 | 6.3 |
| With_family_and_doctor | 28 | 13.3 | 13.6 |
| With_doctor | 56 | 26.7 | 27.2 |
| Doctor_made | 64 | 30.5 | 31.1 |
| Dont_know_or_remember | 5 | 2.4 | 2.4 |
| Scantron_Error | 6 | 2.9 | 2.9 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 46 | 14.6 | 14.9 |
| With_family_or_friends | 19 | 6.0 | 6.2 |
| With_family_and_doctor | 41 | 13.0 | 13.3 |
| With_doctor | 78 | 24.8 | 25.3 |
| Doctor_made | 112 | 35.6 | 36.4 |
| Dont_know_or_remember | 7 | 2.2 | 2.3 |
| Scantron_Error | 5 | 1.6 | 1.6 |
| NA | 7 | 2.2 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 54 | 15.2 | 15.6 |
| With_family_or_friends | 23 | 6.5 | 6.6 |
| With_family_and_doctor | 51 | 14.3 | 14.7 |
| With_doctor | 78 | 21.9 | 22.5 |
| Doctor_made | 109 | 30.6 | 31.5 |
| Dont_know_or_remember | 23 | 6.5 | 6.6 |
| Scantron_Error | 8 | 2.2 | 2.3 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 74 | 12.6 | 12.9 |
| With_family_or_friends | 51 | 8.7 | 8.9 |
| With_family_and_doctor | 80 | 13.7 | 14.0 |
| With_doctor | 133 | 22.7 | 23.3 |
| Doctor_made | 183 | 31.3 | 32.0 |
| Dont_know_or_remember | 39 | 6.7 | 6.8 |
| Scantron_Error | 12 | 2.1 | 2.1 |
| NA | 13 | 2.2 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 241 | 13.7 | 14.1 |
| With_family_or_friends | 109 | 6.2 | 6.4 |
| With_family_and_doctor | 259 | 14.8 | 15.2 |
| With_doctor | 445 | 25.4 | 26.1 |
| Doctor_made | 495 | 28.2 | 29.0 |
| Dont_know_or_remember | 118 | 6.7 | 6.9 |
| Scantron_Error | 41 | 2.3 | 2.4 |
| NA | 46 | 2.6 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "E3")
| n | % | val% | |
|---|---|---|---|
| Alone | 4 | 25.0 | 25.0 |
| With_family_or_friends | 2 | 12.5 | 12.5 |
| With_family_and_doctor | 1 | 6.2 | 6.2 |
| With_doctor | 3 | 18.8 | 18.8 |
| Doctor_made | 5 | 31.2 | 31.2 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 1 | 6.2 | 6.2 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e4 <- as.factor(d[,"e4"])
levels(e4) <- list(Low_risk="1",
Intermediate_risk="2",
High_risk="3",
Unknown_risk="4",
Dont_know_or_remember="88",
Scantron_Error="*")
e4 <- ordered(e4, c("Low_risk","Intermediate_risk","High_risk","Unknown_risk","Dont_know_or_remember","Scantron_Error"))
new.d <- data.frame(new.d, e4)
new.d <- apply_labels(new.d, e4 = "how aggressive")
temp.d <- data.frame (new.d, e4)
result<-questionr::freq(temp.d$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 1280 | 36.0 | 36.7 |
| Intermediate_risk | 594 | 16.7 | 17.0 |
| High_risk | 787 | 22.1 | 22.5 |
| Unknown_risk | 335 | 9.4 | 9.6 |
| Dont_know_or_remember | 488 | 13.7 | 14.0 |
| Scantron_Error | 7 | 0.2 | 0.2 |
| NA | 66 | 1.9 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 128 | 39.9 | 40.4 |
| Intermediate_risk | 50 | 15.6 | 15.8 |
| High_risk | 73 | 22.7 | 23.0 |
| Unknown_risk | 31 | 9.7 | 9.8 |
| Dont_know_or_remember | 35 | 10.9 | 11.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 88 | 41.9 | 42.1 |
| Intermediate_risk | 51 | 24.3 | 24.4 |
| High_risk | 39 | 18.6 | 18.7 |
| Unknown_risk | 13 | 6.2 | 6.2 |
| Dont_know_or_remember | 17 | 8.1 | 8.1 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 1 | 0.5 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 97 | 30.8 | 31.5 |
| Intermediate_risk | 58 | 18.4 | 18.8 |
| High_risk | 102 | 32.4 | 33.1 |
| Unknown_risk | 27 | 8.6 | 8.8 |
| Dont_know_or_remember | 22 | 7.0 | 7.1 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 7 | 2.2 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 113 | 31.7 | 32.1 |
| Intermediate_risk | 52 | 14.6 | 14.8 |
| High_risk | 92 | 25.8 | 26.1 |
| Unknown_risk | 51 | 14.3 | 14.5 |
| Dont_know_or_remember | 44 | 12.4 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.1 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 202 | 34.5 | 34.9 |
| Intermediate_risk | 91 | 15.6 | 15.7 |
| High_risk | 114 | 19.5 | 19.7 |
| Unknown_risk | 65 | 11.1 | 11.2 |
| Dont_know_or_remember | 105 | 17.9 | 18.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 7 | 1.2 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 647 | 36.9 | 37.8 |
| Intermediate_risk | 290 | 16.5 | 16.9 |
| High_risk | 363 | 20.7 | 21.2 |
| Unknown_risk | 145 | 8.3 | 8.5 |
| Dont_know_or_remember | 263 | 15.0 | 15.4 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 43 | 2.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e4")
| n | % | val% | |
|---|---|---|---|
| Low_risk | 5 | 31.2 | 31.2 |
| Intermediate_risk | 2 | 12.5 | 12.5 |
| High_risk | 4 | 25.0 | 25.0 |
| Unknown_risk | 3 | 18.8 | 18.8 |
| Dont_know_or_remember | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e5 <- as.factor(d[,"e5"])
levels(e5) <- list(Six_less="1",
Seven="2",
Eight_to_ten="3",
Dont_know="88",
Scantron_Error="*")
e5 <- ordered(e5, c("Six_less","Seven","Eight_to_ten","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e5)
new.d <- apply_labels(new.d, e5 = "Gleason score")
temp.d <- data.frame (new.d, e5)
result<-questionr::freq(temp.d$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 689 | 19.4 | 20.1 |
| Seven | 580 | 16.3 | 16.9 |
| Eight_to_ten | 516 | 14.5 | 15.0 |
| Dont_know | 1644 | 46.2 | 47.9 |
| Scantron_Error | 6 | 0.2 | 0.2 |
| NA | 122 | 3.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 57 | 17.8 | 18.1 |
| Seven | 52 | 16.2 | 16.5 |
| Eight_to_ten | 62 | 19.3 | 19.7 |
| Dont_know | 144 | 44.9 | 45.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 48 | 22.9 | 23.4 |
| Seven | 43 | 20.5 | 21.0 |
| Eight_to_ten | 29 | 13.8 | 14.1 |
| Dont_know | 84 | 40.0 | 41.0 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 67 | 21.3 | 22.1 |
| Seven | 61 | 19.4 | 20.1 |
| Eight_to_ten | 57 | 18.1 | 18.8 |
| Dont_know | 118 | 37.5 | 38.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 53 | 14.9 | 15.3 |
| Seven | 63 | 17.7 | 18.2 |
| Eight_to_ten | 47 | 13.2 | 13.6 |
| Dont_know | 183 | 51.4 | 52.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 2.8 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 95 | 16.2 | 16.8 |
| Seven | 88 | 15.0 | 15.6 |
| Eight_to_ten | 63 | 10.8 | 11.2 |
| Dont_know | 317 | 54.2 | 56.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 21 | 3.6 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 364 | 20.8 | 21.6 |
| Seven | 271 | 15.5 | 16.1 |
| Eight_to_ten | 255 | 14.5 | 15.1 |
| Dont_know | 793 | 45.2 | 47.0 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 67 | 3.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e5")
| n | % | val% | |
|---|---|---|---|
| Six_less | 5 | 31.2 | 33.3 |
| Seven | 2 | 12.5 | 13.3 |
| Eight_to_ten | 3 | 18.8 | 20.0 |
| Dont_know | 5 | 31.2 | 33.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e6 <- as.factor(d[,"e6"])
levels(e6) <- list(Localized="1",
Regional="2",
Distant="3",
Dont_know="88",
Scantron_Error="*")
e6 <- ordered(e6, c("Localized","Regional","Distant","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e6)
new.d <- apply_labels(new.d, e6 = "Stage")
temp.d <- data.frame (new.d, e6)
result<-questionr::freq(temp.d$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 2451 | 68.9 | 71.0 |
| Regional | 149 | 4.2 | 4.3 |
| Distant | 67 | 1.9 | 1.9 |
| Dont_know | 782 | 22.0 | 22.7 |
| Scantron_Error | 3 | 0.1 | 0.1 |
| NA | 105 | 3.0 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 236 | 73.5 | 74.7 |
| Regional | 17 | 5.3 | 5.4 |
| Distant | 5 | 1.6 | 1.6 |
| Dont_know | 58 | 18.1 | 18.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 1.6 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 167 | 79.5 | 81.1 |
| Regional | 2 | 1.0 | 1.0 |
| Distant | 7 | 3.3 | 3.4 |
| Dont_know | 30 | 14.3 | 14.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 229 | 72.7 | 75.1 |
| Regional | 19 | 6.0 | 6.2 |
| Distant | 9 | 2.9 | 3.0 |
| Dont_know | 48 | 15.2 | 15.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 3.2 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 222 | 62.4 | 64.7 |
| Regional | 18 | 5.1 | 5.2 |
| Distant | 11 | 3.1 | 3.2 |
| Dont_know | 91 | 25.6 | 26.5 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 13 | 3.7 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 378 | 64.6 | 66.5 |
| Regional | 20 | 3.4 | 3.5 |
| Distant | 5 | 0.9 | 0.9 |
| Dont_know | 165 | 28.2 | 29.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 2.9 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 1208 | 68.9 | 71.1 |
| Regional | 72 | 4.1 | 4.2 |
| Distant | 30 | 1.7 | 1.8 |
| Dont_know | 386 | 22.0 | 22.7 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 56 | 3.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e6")
| n | % | val% | |
|---|---|---|---|
| Localized | 11 | 68.8 | 68.8 |
| Regional | 1 | 6.2 | 6.2 |
| Distant | 0 | 0.0 | 0.0 |
| Dont_know | 4 | 25.0 | 25.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e7 <- as.factor(d[,"e7"])
levels(e7) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
e7 <- ordered(e7, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e7)
new.d <- apply_labels(new.d, e7 = "Stage")
temp.d <- data.frame (new.d, e7)
result<-questionr::freq(temp.d$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 1280 | 36.0 | 37.2 |
| Yes | 1328 | 37.3 | 38.6 |
| Dont_know | 826 | 23.2 | 24.0 |
| Scantron_Error | 5 | 0.1 | 0.1 |
| NA | 118 | 3.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 143 | 44.5 | 45.4 |
| Yes | 116 | 36.1 | 36.8 |
| Dont_know | 56 | 17.4 | 17.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 86 | 41.0 | 41.5 |
| Yes | 90 | 42.9 | 43.5 |
| Dont_know | 31 | 14.8 | 15.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 1.4 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 148 | 47.0 | 49.2 |
| Yes | 116 | 36.8 | 38.5 |
| Dont_know | 37 | 11.7 | 12.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 120 | 33.7 | 35.1 |
| Yes | 121 | 34.0 | 35.4 |
| Dont_know | 100 | 28.1 | 29.2 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 14 | 3.9 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 173 | 29.6 | 30.6 |
| Yes | 235 | 40.2 | 41.6 |
| Dont_know | 156 | 26.7 | 27.6 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 20 | 3.4 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 600 | 34.2 | 35.4 |
| Yes | 646 | 36.8 | 38.2 |
| Dont_know | 444 | 25.3 | 26.2 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 61 | 3.5 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e7")
| n | % | val% | |
|---|---|---|---|
| No | 10 | 62.5 | 62.5 |
| Yes | 4 | 25.0 | 25.0 |
| Dont_know | 2 | 12.5 | 12.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e8 <- as.factor(d[,"e8"])
levels(e8) <- list(Alone="1",
With_family_or_friends="2",
With_family_and_doctor="3",
With_doctor="4",
Doctor_made="5",
Dont_know_or_remember="88",
Scantron_Error="*")
e8 <- ordered(e8, c("Alone","With_family_or_friends","With_family_and_doctor","With_doctor","Doctor_made","Dont_know_or_remember","Scantron_Error"))
new.d <- data.frame(new.d, e8)
new.d <- apply_labels(new.d, e8 = "treatment decision")
temp.d <- data.frame (new.d, e8)
result<-questionr::freq(temp.d$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 466 | 13.1 | 13.7 |
| With_family_or_friends | 506 | 14.2 | 14.8 |
| With_family_and_doctor | 1278 | 35.9 | 37.5 |
| With_doctor | 802 | 22.5 | 23.5 |
| Doctor_made | 310 | 8.7 | 9.1 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 49 | 1.4 | 1.4 |
| NA | 146 | 4.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 47 | 14.6 | 15.1 |
| With_family_or_friends | 39 | 12.1 | 12.5 |
| With_family_and_doctor | 116 | 36.1 | 37.2 |
| With_doctor | 72 | 22.4 | 23.1 |
| Doctor_made | 34 | 10.6 | 10.9 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 4 | 1.2 | 1.3 |
| NA | 9 | 2.8 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 23 | 11.0 | 11.2 |
| With_family_or_friends | 28 | 13.3 | 13.7 |
| With_family_and_doctor | 86 | 41.0 | 42.0 |
| With_doctor | 49 | 23.3 | 23.9 |
| Doctor_made | 16 | 7.6 | 7.8 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 3 | 1.4 | 1.5 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 30 | 9.5 | 9.8 |
| With_family_or_friends | 43 | 13.7 | 14.1 |
| With_family_and_doctor | 112 | 35.6 | 36.7 |
| With_doctor | 82 | 26.0 | 26.9 |
| Doctor_made | 31 | 9.8 | 10.2 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 7 | 2.2 | 2.3 |
| NA | 10 | 3.2 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 56 | 15.7 | 16.7 |
| With_family_or_friends | 50 | 14.0 | 14.9 |
| With_family_and_doctor | 115 | 32.3 | 34.3 |
| With_doctor | 72 | 20.2 | 21.5 |
| Doctor_made | 36 | 10.1 | 10.7 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 6 | 1.7 | 1.8 |
| NA | 21 | 5.9 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 102 | 17.4 | 18.2 |
| With_family_or_friends | 82 | 14.0 | 14.6 |
| With_family_and_doctor | 188 | 32.1 | 33.6 |
| With_doctor | 121 | 20.7 | 21.6 |
| Doctor_made | 63 | 10.8 | 11.2 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 4 | 0.7 | 0.7 |
| NA | 25 | 4.3 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 206 | 11.7 | 12.3 |
| With_family_or_friends | 263 | 15.0 | 15.7 |
| With_family_and_doctor | 657 | 37.5 | 39.1 |
| With_doctor | 400 | 22.8 | 23.8 |
| Doctor_made | 130 | 7.4 | 7.7 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 24 | 1.4 | 1.4 |
| NA | 74 | 4.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e8")
| n | % | val% | |
|---|---|---|---|
| Alone | 2 | 12.5 | 14.3 |
| With_family_or_friends | 1 | 6.2 | 7.1 |
| With_family_and_doctor | 4 | 25.0 | 28.6 |
| With_doctor | 6 | 37.5 | 42.9 |
| Doctor_made | 0 | 0.0 | 0.0 |
| Dont_know_or_remember | 0 | 0.0 | 0.0 |
| Scantron_Error | 1 | 6.2 | 7.1 |
| NA | 2 | 12.5 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e9_1 <- as.factor(d[,"e9_1"])
levels(e9_1) <- list(Best_for_cure="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_1)
new.d <- apply_labels(new.d, e9_1 = "Best for cure")
temp.d <- data.frame (new.d, e9_1)
result<-questionr::freq(temp.d$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 3064 | 86.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 493 | 13.9 | NA |
| Total | 3557 | 100.0 | 100 |
e9_2 <- as.factor(d[,"e9_2"])
levels(e9_2) <- list(side_effects_sexual="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_2)
new.d <- apply_labels(new.d, e9_2 = "side effects sexual")
temp.d <- data.frame (new.d, e9_2)
result<-questionr::freq(temp.d$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 1041 | 29.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2516 | 70.7 | NA |
| Total | 3557 | 100.0 | 100 |
e9_3 <- as.factor(d[,"e9_3"])
levels(e9_3) <- list(side_effects_urinary="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_3)
new.d <- apply_labels(new.d, e9_3 = "side effects urinary")
temp.d <- data.frame (new.d, e9_3)
result<-questionr::freq(temp.d$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 933 | 26.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2624 | 73.8 | NA |
| Total | 3557 | 100.0 | 100 |
e9_4 <- as.factor(d[,"e9_4"])
levels(e9_4) <- list(side_effects_bowel="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_4)
new.d <- apply_labels(new.d, e9_4 = "side effects bowel")
temp.d <- data.frame (new.d, e9_4)
result<-questionr::freq(temp.d$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 447 | 12.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3110 | 87.4 | NA |
| Total | 3557 | 100.0 | 100 |
e9_5 <- as.factor(d[,"e9_5"])
levels(e9_5) <- list(financial_cost="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_5)
new.d <- apply_labels(new.d, e9_5 = "financial cost")
temp.d <- data.frame (new.d, e9_5)
result<-questionr::freq(temp.d$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 213 | 6 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3344 | 94 | NA |
| Total | 3557 | 100 | 100 |
e9_6 <- as.factor(d[,"e9_6"])
levels(e9_6) <- list(time_and_travel="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_6)
new.d <- apply_labels(new.d, e9_6 = "time and travel")
temp.d <- data.frame (new.d, e9_6)
result<-questionr::freq(temp.d$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 376 | 10.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3181 | 89.4 | NA |
| Total | 3557 | 100.0 | 100 |
e9_7 <- as.factor(d[,"e9_7"])
levels(e9_7) <- list(recovery_time="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_7)
new.d <- apply_labels(new.d, e9_7 = "recovery time")
temp.d <- data.frame (new.d, e9_7)
result<-questionr::freq(temp.d$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 678 | 19.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2879 | 80.9 | NA |
| Total | 3557 | 100.0 | 100 |
e9_8 <- as.factor(d[,"e9_8"])
levels(e9_8) <- list(time_away_from_work="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_8)
new.d <- apply_labels(new.d, e9_8 = "time away from work")
temp.d <- data.frame (new.d, e9_8)
result<-questionr::freq(temp.d$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 284 | 8 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3273 | 92 | NA |
| Total | 3557 | 100 | 100 |
e9_9 <- as.factor(d[,"e9_9"])
levels(e9_9) <- list(family_burden="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_9)
new.d <- apply_labels(new.d, e9_9 = "family burden")
temp.d <- data.frame (new.d, e9_9)
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
e9_10 <- as.factor(d[,"e9_10"])
levels(e9_10) <- list(Reduce_worry_concern="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e9_10)
new.d <- apply_labels(new.d, e9_10 = "Reduce worry and concern")
temp.d <- data.frame (new.d, e9_10)
result<-questionr::freq(temp.d$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 1518 | 42.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2039 | 57.3 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 294 | 91.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 27 | 8.4 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 94 | 29.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 227 | 70.7 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 86 | 26.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 235 | 73.2 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 31 | 9.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 290 | 90.3 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 12 | 3.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 309 | 96.3 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 22 | 6.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 299 | 93.1 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 45 | 14 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 276 | 86 | NA |
| Total | 321 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 23 | 7.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 298 | 92.8 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 172 | 53.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 149 | 46.4 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 185 | 88.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 25 | 11.9 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 71 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 139 | 66.2 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 64 | 30.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 146 | 69.5 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 38 | 18.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 172 | 81.9 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 8 | 3.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 202 | 96.2 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 18 | 8.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 192 | 91.4 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 40 | 19 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 170 | 81 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 16 | 7.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 194 | 92.4 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 81 | 38.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 129 | 61.4 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 266 | 84.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 49 | 15.6 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 100 | 31.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 215 | 68.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 90 | 28.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 225 | 71.4 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 44 | 14 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 271 | 86 | NA |
| Total | 315 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 11 | 3.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 304 | 96.5 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 24 | 7.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 291 | 92.4 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 56 | 17.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 259 | 82.2 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 27 | 8.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 288 | 91.4 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 152 | 48.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 163 | 51.7 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 303 | 85.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 53 | 14.9 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 106 | 29.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 250 | 70.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 86 | 24.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 270 | 75.8 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 45 | 12.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 311 | 87.4 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 22 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 334 | 93.8 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 35 | 9.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 321 | 90.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 68 | 19.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 288 | 80.9 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 27 | 7.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 329 | 92.4 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 140 | 39.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 216 | 60.7 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 506 | 86.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 79 | 13.5 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 124 | 21.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 461 | 78.8 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 123 | 21 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 462 | 79 | NA |
| Total | 585 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 49 | 8.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 536 | 91.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 42 | 7.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 543 | 92.8 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 63 | 10.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 522 | 89.2 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 98 | 16.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 487 | 83.2 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 41 | 7 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 544 | 93 | NA |
| Total | 585 | 100 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 232 | 39.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 353 | 60.3 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 1497 | 85.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 257 | 14.7 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 538 | 30.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1216 | 69.3 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 476 | 27.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1278 | 72.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 236 | 13.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1518 | 86.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 117 | 6.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1637 | 93.3 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 213 | 12.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1541 | 87.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 366 | 20.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1388 | 79.1 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 147 | 8.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1607 | 91.6 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 731 | 41.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1023 | 58.3 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e9_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Best chance for cure of my cancer")
| n | % | val% | |
|---|---|---|---|
| Best_for_cure | 13 | 81.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3 | 18.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Minimize side effects related to sexual function")
| n | % | val% | |
|---|---|---|---|
| side_effects_sexual | 8 | 50 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 8 | 50 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Minimize side effects related to urinary function")
| n | % | val% | |
|---|---|---|---|
| side_effects_urinary | 8 | 50 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 8 | 50 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Minimize side effects related to bowel function")
| n | % | val% | |
|---|---|---|---|
| side_effects_bowel | 4 | 25 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 12 | 75 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e9_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Minimize financial cost")
| n | % | val% | |
|---|---|---|---|
| financial_cost | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Amount of time and travel required to receive treatments")
| n | % | val% | |
|---|---|---|---|
| time_and_travel | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Length of recovery time")
| n | % | val% | |
|---|---|---|---|
| recovery_time | 5 | 31.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Amount of time away from work")
| n | % | val% | |
|---|---|---|---|
| time_away_from_work | 3 | 18.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.d$e9_9,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "9. Burden on family members")
| n | % | val% | |
|---|---|---|---|
| family_burden | 515 | 14.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3042 | 85.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e9_10,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "10. Reduce worry and concern about cancer")
| n | % | val% | |
|---|---|---|---|
| Reduce_worry_concern | 10 | 62.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 6 | 37.5 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e10_1 <- as.factor(d[,"e10_1"])
levels(e10_1) <- list(no_treatment="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_1)
new.d <- apply_labels(new.d, e10_1 = "no treatment")
temp.d <- data.frame (new.d, e10_1)
result<-questionr::freq(temp.d$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 201 | 5.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3356 | 94.3 | NA |
| Total | 3557 | 100.0 | 100 |
e10_2 <- as.factor(d[,"e10_2"])
levels(e10_2) <- list(Active_Surveillance="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_2)
new.d <- apply_labels(new.d, e10_2 = "Active Surveillance")
temp.d <- data.frame (new.d, e10_2)
result<-questionr::freq(temp.d$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 569 | 16 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 2988 | 84 | NA |
| Total | 3557 | 100 | 100 |
e10_3 <- as.factor(d[,"e10_3"])
levels(e10_3) <- list(prostatectomy="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_3)
new.d <- apply_labels(new.d, e10_3 = "prostatectomy")
temp.d <- data.frame (new.d, e10_3)
result<-questionr::freq(temp.d$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 1133 | 31.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2424 | 68.1 | NA |
| Total | 3557 | 100.0 | 100 |
e10_4 <- as.factor(d[,"e10_4"])
levels(e10_4) <- list(Radiation="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_4)
new.d <- apply_labels(new.d, e10_4 = "Radiation")
temp.d <- data.frame (new.d, e10_4)
result<-questionr::freq(temp.d$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 1396 | 39.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2161 | 60.8 | NA |
| Total | 3557 | 100.0 | 100 |
e10_5 <- as.factor(d[,"e10_5"])
levels(e10_5) <- list(Hormonal_treatments="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5)
new.d <- apply_labels(new.d, e10_5 = "Hormonal treatments")
temp.d <- data.frame (new.d, e10_5)
result<-questionr::freq(temp.d$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 443 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3114 | 87.5 | NA |
| Total | 3557 | 100.0 | 100 |
e10_6 <- as.factor(d[,"e10_6"])
levels(e10_6) <- list(Provenge_immunotherapy="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_6)
new.d <- apply_labels(new.d, e10_6 = "Provenge immunotherapy")
temp.d <- data.frame (new.d, e10_6)
result<-questionr::freq(temp.d$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 37 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3520 | 99 | NA |
| Total | 3557 | 100 | 100 |
e10_7 <- as.factor(d[,"e10_7"])
levels(e10_7) <- list(Chemotherapy="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_7)
new.d <- apply_labels(new.d, e10_7 = "Chemotherapy")
temp.d <- data.frame (new.d, e10_7)
result<-questionr::freq(temp.d$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 115 | 3.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3442 | 96.8 | NA |
| Total | 3557 | 100.0 | 100 |
e10_8 <- as.factor(d[,"e10_8"])
levels(e10_8) <- list(Other="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_8)
new.d <- apply_labels(new.d, e10_8 = "Other")
temp.d <- data.frame (new.d, e10_8)
result<-questionr::freq(temp.d$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 192 | 5.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3365 | 94.6 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 18 | 5.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 303 | 94.4 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 52 | 16.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 269 | 83.8 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 150 | 46.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 171 | 53.3 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 114 | 35.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 207 | 64.5 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 56 | 17.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 265 | 82.6 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 2 | 0.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 319 | 99.4 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 13 | 4 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 308 | 96 | NA |
| Total | 321 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 10 | 3.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 311 | 96.9 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 9 | 4.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 201 | 95.7 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 46 | 21.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 164 | 78.1 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 51 | 24.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 159 | 75.7 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 84 | 40 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 126 | 60 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 28 | 13.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 182 | 86.7 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 2 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 208 | 99 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 5 | 2.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 205 | 97.6 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 12 | 5.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 198 | 94.3 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 21 | 6.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 294 | 93.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 60 | 19 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 255 | 81 | NA |
| Total | 315 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 133 | 42.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 182 | 57.8 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 108 | 34.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 207 | 65.7 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 52 | 16.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 263 | 83.5 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 4 | 1.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 311 | 98.7 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 9 | 2.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 306 | 97.1 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 10 | 3.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 305 | 96.8 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 25 | 7 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 331 | 93 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 55 | 15.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 301 | 84.6 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 124 | 34.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 232 | 65.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 135 | 37.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 221 | 62.1 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 55 | 15.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 301 | 84.6 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 4 | 1.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 352 | 98.9 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 15 | 4.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 341 | 95.8 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 17 | 4.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 339 | 95.2 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 39 | 6.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 546 | 93.3 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 74 | 12.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 511 | 87.4 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 186 | 31.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 399 | 68.2 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 201 | 34.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 384 | 65.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 55 | 9.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 530 | 90.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 7 | 1.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 578 | 98.8 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 21 | 3.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 564 | 96.4 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 38 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 547 | 93.5 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 89 | 5.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1665 | 94.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 279 | 15.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1475 | 84.1 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 483 | 27.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1271 | 72.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 746 | 42.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1008 | 57.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 195 | 11.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1559 | 88.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 18 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 1736 | 99 | NA |
| Total | 1754 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 51 | 2.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1703 | 97.1 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 103 | 5.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1651 | 94.1 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e10_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Haven’t had any treatment yet (and not specifically on active surveillance or watchful waiting).")
| n | % | val% | |
|---|---|---|---|
| no_treatment | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Active Surveillance or watchful waiting")
| n | % | val% | |
|---|---|---|---|
| Active_Surveillance | 3 | 18.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Prostate surgery (prostatectomy)")
| n | % | val% | |
|---|---|---|---|
| prostatectomy | 6 | 37.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 10 | 62.5 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Radiation to the prostate")
| n | % | val% | |
|---|---|---|---|
| Radiation | 8 | 50 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 8 | 50 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. Hormonal treatments")
| n | % | val% | |
|---|---|---|---|
| Hormonal_treatments | 2 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 87.5 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "6. Provenge/immunotherapy (Sipuleucel T)")
| n | % | val% | |
|---|---|---|---|
| Provenge_immunotherapy | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "7. Chemotherapy (docetaxel, cabazitaxel, other chemotherapy)")
| n | % | val% | |
|---|---|---|---|
| Chemotherapy | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "8. Other treatments to the prostate ")
| n | % | val% | |
|---|---|---|---|
| Other | 2 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 87.5 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e10_3_1 <- as.factor(d[,"e10_3_1"])
levels(e10_3_1) <- list(Robotic_laproscopic_surgery="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_3_1)
new.d <- apply_labels(new.d, e10_3_1 = "Robotic or laproscopic surgery")
temp.d <- data.frame (new.d, e10_3_1)
result<-questionr::freq(temp.d$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 1174 | 33 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 2383 | 67 | NA |
| Total | 3557 | 100 | 100 |
e10_3_2 <- as.factor(d[,"e10_3_2"])
levels(e10_3_2) <- list(Open_surgical_removal="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_3_2)
new.d <- apply_labels(new.d, e10_3_2 = "Open surgical removal")
temp.d <- data.frame (new.d, e10_3_2)
result<-questionr::freq(temp.d$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 194 | 5.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3363 | 94.5 | NA |
| Total | 3557 | 100.0 | 100 |
e10_3_3 <- as.factor(d[,"e10_3_3"])
levels(e10_3_3) <- list(unsure_of_type="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_3_3)
new.d <- apply_labels(new.d, e10_3_3 = "unsure of type")
temp.d <- data.frame (new.d, e10_3_3)
result<-questionr::freq(temp.d$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 226 | 6.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3331 | 93.6 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 165 | 51.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 156 | 48.6 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 7 | 2.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 314 | 97.8 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 8 | 2.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 313 | 97.5 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 46 | 21.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 164 | 78.1 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 9 | 4.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 201 | 95.7 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 10 | 4.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 200 | 95.2 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 151 | 47.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 164 | 52.1 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 11 | 3.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 304 | 96.5 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 13 | 4.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 302 | 95.9 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 121 | 34 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 235 | 66 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 32 | 9 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 324 | 91 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 15 | 4.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 341 | 95.8 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 206 | 35.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 379 | 64.8 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 47 | 8 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 538 | 92 | NA |
| Total | 585 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 53 | 9.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 532 | 90.9 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 476 | 27.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1278 | 72.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 87 | 5 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 1667 | 95 | NA |
| Total | 1754 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 127 | 7.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1627 | 92.8 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e10_3_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Robotic or laproscopic surgery resulting in removal of the prostate")
| n | % | val% | |
|---|---|---|---|
| Robotic_laproscopic_surgery | 9 | 56.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 7 | 43.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. Open surgical removal of the prostate (using a long incision)")
| n | % | val% | |
|---|---|---|---|
| Open_surgical_removal | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_3_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Had surgery but unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_of_type | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
rm(temp.dd)
e10_4_1 <- as.factor(d[,"e10_4_1"])
levels(e10_4_1) <- list(External_beam_radiation="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_4_1)
new.d <- apply_labels(new.d, e10_4_1 = "External beam radiation")
temp.d <- data.frame (new.d, e10_4_1)
result<-questionr::freq(temp.d$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 1268 | 35.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2289 | 64.4 | NA |
| Total | 3557 | 100.0 | 100 |
e10_4_2 <- as.factor(d[,"e10_4_2"])
levels(e10_4_2) <- list(brachytherapy="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_4_2)
new.d <- apply_labels(new.d, e10_4_2 = "brachytherapy")
temp.d <- data.frame (new.d, e10_4_2)
result<-questionr::freq(temp.d$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 633 | 17.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2924 | 82.2 | NA |
| Total | 3557 | 100.0 | 100 |
e10_4_3 <- as.factor(d[,"e10_4_3"])
levels(e10_4_3) <- list(Other_types="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_4_3)
new.d <- apply_labels(new.d, e10_4_3 = "Other types")
temp.d <- data.frame (new.d, e10_4_3)
result<-questionr::freq(temp.d$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 214 | 6 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3343 | 94 | NA |
| Total | 3557 | 100 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 115 | 35.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 206 | 64.2 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 24 | 7.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 297 | 92.5 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 13 | 4 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 308 | 96 | NA |
| Total | 321 | 100 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 78 | 37.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 132 | 62.9 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 47 | 22.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 163 | 77.6 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 12 | 5.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 198 | 94.3 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 95 | 30.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 220 | 69.8 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 34 | 10.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 281 | 89.2 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 13 | 4.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 302 | 95.9 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 124 | 34.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 232 | 65.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 28 | 7.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 328 | 92.1 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 24 | 6.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 332 | 93.3 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 209 | 35.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 376 | 64.3 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 50 | 8.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 535 | 91.5 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 43 | 7.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 542 | 92.6 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 640 | 36.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1114 | 63.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 448 | 25.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1306 | 74.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 108 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1646 | 93.8 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e10_4_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. External beam radiation")
| n | % | val% | |
|---|---|---|---|
| External_beam_radiation | 7 | 43.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 9 | 56.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. brachytherapy")
| n | % | val% | |
|---|---|---|---|
| brachytherapy | 2 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 87.5 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_4_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Other types")
| n | % | val% | |
|---|---|---|---|
| Other_types | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e10_5_1 <- as.factor(d[,"e10_5_1"])
levels(e10_5_1) <- list(Hormone_shots="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5_1)
new.d <- apply_labels(new.d, e10_5_1 = "Hormone shots")
temp.d <- data.frame (new.d, e10_5_1)
result<-questionr::freq(temp.d$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 622 | 17.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2935 | 82.5 | NA |
| Total | 3557 | 100.0 | 100 |
e10_5_2 <- as.factor(d[,"e10_5_2"])
levels(e10_5_2) <- list(orchiectomy="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5_2)
new.d <- apply_labels(new.d, e10_5_2 = "orchiectomy")
temp.d <- data.frame (new.d, e10_5_2)
result<-questionr::freq(temp.d$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 46 | 1.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3511 | 98.7 | NA |
| Total | 3557 | 100.0 | 100 |
e10_5_3 <- as.factor(d[,"e10_5_3"])
levels(e10_5_3) <- list(Casodex_Eulexin="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5_3)
new.d <- apply_labels(new.d, e10_5_3 = "Casodex or Eulexin pills")
temp.d <- data.frame (new.d, e10_5_3)
result<-questionr::freq(temp.d$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 78 | 2.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3479 | 97.8 | NA |
| Total | 3557 | 100.0 | 100 |
e10_5_4 <- as.factor(d[,"e10_5_4"])
levels(e10_5_4) <- list(Zytiga_Xtandi="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5_4)
new.d <- apply_labels(new.d, e10_5_4 = "Zytiga or Xtandi pills")
temp.d <- data.frame (new.d, e10_5_4)
result<-questionr::freq(temp.d$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 56 | 1.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3501 | 98.4 | NA |
| Total | 3557 | 100.0 | 100 |
e10_5_5 <- as.factor(d[,"e10_5_5"])
levels(e10_5_5) <- list(unsure_type="1",
Scantron_Error="*")
new.d <- data.frame(new.d, e10_5_5)
new.d <- apply_labels(new.d, e10_5_5 = "unsure of type")
temp.d <- data.frame (new.d, e10_5_5)
result<-questionr::freq(temp.d$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 182 | 5.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3375 | 94.9 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 72 | 22.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 249 | 77.6 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 1 | 0.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 320 | 99.7 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 11 | 3.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 310 | 96.6 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 5 | 1.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 316 | 98.4 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 10 | 3.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 311 | 96.9 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 53 | 25.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 157 | 74.8 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 210 | 100 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 3 | 1.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 207 | 98.6 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 2 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 208 | 99 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 5 | 2.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 205 | 97.6 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 62 | 19.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 253 | 80.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 3 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 312 | 99 | NA |
| Total | 315 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 14 | 4.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 301 | 95.6 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 8 | 2.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 307 | 97.5 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 12 | 3.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 303 | 96.2 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 64 | 18 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 292 | 82 | NA |
| Total | 356 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 6 | 1.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 350 | 98.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 6 | 1.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 350 | 98.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 5 | 1.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 351 | 98.6 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 21 | 5.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 335 | 94.1 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 99 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 486 | 83.1 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 11 | 1.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 574 | 98.1 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 8 | 1.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 577 | 98.6 | NA |
| Total | 585 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 6 | 1 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 579 | 99 | NA |
| Total | 585 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 44 | 7.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 541 | 92.5 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 269 | 15.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1485 | 84.7 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 25 | 1.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1729 | 98.6 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 36 | 2.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1718 | 97.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 30 | 1.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1724 | 98.3 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 90 | 5.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1664 | 94.9 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e10_5_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "1. Hormone shots")
| n | % | val% | |
|---|---|---|---|
| Hormone_shots | 3 | 18.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 13 | 81.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$e10_5_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "2. orchiectomy")
| n | % | val% | |
|---|---|---|---|
| orchiectomy | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "3. Casodex or Eulexin pills")
| n | % | val% | |
|---|---|---|---|
| Casodex_Eulexin | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "4. Zytiga or Xtandi pills")
| n | % | val% | |
|---|---|---|---|
| Zytiga_Xtandi | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$e10_5_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "5. unsure of type")
| n | % | val% | |
|---|---|---|---|
| unsure_type | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
rm(temp.dd)
e11a <- as.factor(d[,"e11a"])
levels(e11a) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11a)
new.d <- apply_labels(new.d, e11a = "all info")
temp.d <- data.frame (new.d, e11a)
result<-questionr::freq(temp.d$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 111 | 3.1 | 3.3 |
| A_little_bit | 126 | 3.5 | 3.7 |
| Somewhat | 415 | 11.7 | 12.2 |
| Quite_a_bit | 874 | 24.6 | 25.7 |
| Very_much | 1865 | 52.4 | 54.9 |
| Scantron_Error | 6 | 0.2 | 0.2 |
| NA | 160 | 4.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
e11b <- as.factor(d[,"e11b"])
levels(e11b) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11b)
new.d <- apply_labels(new.d, e11b = "be told about effects")
temp.d <- data.frame (new.d, e11b)
result<-questionr::freq(temp.d$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 82 | 2.3 | 2.4 |
| A_little_bit | 140 | 3.9 | 4.1 |
| Somewhat | 407 | 11.4 | 11.9 |
| Quite_a_bit | 834 | 23.4 | 24.5 |
| Very_much | 1940 | 54.5 | 56.9 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 150 | 4.2 | NA |
| Total | 3557 | 100.0 | 100.0 |
e11c <- as.factor(d[,"e11c"])
levels(e11c) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11c)
new.d <- apply_labels(new.d, e11c = "right questions to ask")
temp.d <- data.frame (new.d, e11c)
result<-questionr::freq(temp.d$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 336 | 9.4 | 9.9 |
| A_little_bit | 405 | 11.4 | 11.9 |
| Somewhat | 1123 | 31.6 | 33.0 |
| Quite_a_bit | 668 | 18.8 | 19.6 |
| Very_much | 856 | 24.1 | 25.2 |
| Scantron_Error | 12 | 0.3 | 0.4 |
| NA | 157 | 4.4 | NA |
| Total | 3557 | 100.0 | 100.0 |
e11d <- as.factor(d[,"e11d"])
levels(e11d) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11d)
new.d <- apply_labels(new.d, e11d = "enough time to decide")
temp.d <- data.frame (new.d, e11d)
result<-questionr::freq(temp.d$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 87 | 2.4 | 2.6 |
| A_little_bit | 141 | 4.0 | 4.1 |
| Somewhat | 529 | 14.9 | 15.6 |
| Quite_a_bit | 847 | 23.8 | 24.9 |
| Very_much | 1787 | 50.2 | 52.6 |
| Scantron_Error | 7 | 0.2 | 0.2 |
| NA | 159 | 4.5 | NA |
| Total | 3557 | 100.0 | 100.0 |
e11e <- as.factor(d[,"e11e"])
levels(e11e) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11e)
new.d <- apply_labels(new.d, e11e = "satisfied with the choices")
temp.d <- data.frame (new.d, e11e)
result<-questionr::freq(temp.d$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 137 | 3.9 | 4.0 |
| A_little_bit | 125 | 3.5 | 3.7 |
| Somewhat | 413 | 11.6 | 12.1 |
| Quite_a_bit | 518 | 14.6 | 15.2 |
| Very_much | 2205 | 62.0 | 64.8 |
| Scantron_Error | 5 | 0.1 | 0.1 |
| NA | 154 | 4.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
e11f <- as.factor(d[,"e11f"])
levels(e11f) <- list(Not_at_all="1",
A_little_bit="2",
Somewhat="3",
Quite_a_bit="4",
Very_much="5",
Scantron_Error="*")
new.d <- data.frame(new.d, e11f)
new.d <- apply_labels(new.d, e11f = "would recommend")
temp.d <- data.frame (new.d, e11f)
result<-questionr::freq(temp.d$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 191 | 5.4 | 5.7 |
| A_little_bit | 133 | 3.7 | 3.9 |
| Somewhat | 495 | 13.9 | 14.7 |
| Quite_a_bit | 461 | 13.0 | 13.7 |
| Very_much | 2092 | 58.8 | 62.0 |
| Scantron_Error | 4 | 0.1 | 0.1 |
| NA | 181 | 5.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 9 | 2.8 | 2.8 |
| A_little_bit | 19 | 5.9 | 6.0 |
| Somewhat | 45 | 14.0 | 14.2 |
| Quite_a_bit | 102 | 31.8 | 32.2 |
| Very_much | 142 | 44.2 | 44.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 6 | 1.9 | 1.9 |
| A_little_bit | 18 | 5.6 | 5.7 |
| Somewhat | 44 | 13.7 | 13.9 |
| Quite_a_bit | 97 | 30.2 | 30.6 |
| Very_much | 152 | 47.4 | 47.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 33 | 10.3 | 10.4 |
| A_little_bit | 55 | 17.1 | 17.3 |
| Somewhat | 99 | 30.8 | 31.1 |
| Quite_a_bit | 73 | 22.7 | 23.0 |
| Very_much | 58 | 18.1 | 18.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 11 | 3.4 | 3.5 |
| A_little_bit | 9 | 2.8 | 2.8 |
| Somewhat | 53 | 16.5 | 16.7 |
| Quite_a_bit | 98 | 30.5 | 30.8 |
| Very_much | 147 | 45.8 | 46.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 13 | 4.0 | 4.1 |
| A_little_bit | 8 | 2.5 | 2.5 |
| Somewhat | 39 | 12.1 | 12.3 |
| Quite_a_bit | 66 | 20.6 | 20.8 |
| Very_much | 192 | 59.8 | 60.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 13 | 4.0 | 4.1 |
| A_little_bit | 18 | 5.6 | 5.7 |
| Somewhat | 63 | 19.6 | 19.8 |
| Quite_a_bit | 64 | 19.9 | 20.1 |
| Very_much | 160 | 49.8 | 50.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 5 | 2.4 | 2.5 |
| A_little_bit | 2 | 1.0 | 1.0 |
| Somewhat | 24 | 11.4 | 11.8 |
| Quite_a_bit | 52 | 24.8 | 25.5 |
| Very_much | 121 | 57.6 | 59.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 5 | 2.4 | 2.5 |
| A_little_bit | 4 | 1.9 | 2.0 |
| Somewhat | 23 | 11.0 | 11.3 |
| Quite_a_bit | 47 | 22.4 | 23.0 |
| Very_much | 125 | 59.5 | 61.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 6 | 2.9 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 15 | 7.1 | 7.4 |
| A_little_bit | 22 | 10.5 | 10.8 |
| Somewhat | 74 | 35.2 | 36.5 |
| Quite_a_bit | 40 | 19.0 | 19.7 |
| Very_much | 52 | 24.8 | 25.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 3.3 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 2 | 1.0 | 1.0 |
| A_little_bit | 7 | 3.3 | 3.5 |
| Somewhat | 32 | 15.2 | 15.8 |
| Quite_a_bit | 44 | 21.0 | 21.8 |
| Very_much | 117 | 55.7 | 57.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 8 | 3.8 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 7 | 3.3 | 3.4 |
| A_little_bit | 10 | 4.8 | 4.9 |
| Somewhat | 28 | 13.3 | 13.7 |
| Quite_a_bit | 23 | 11.0 | 11.2 |
| Very_much | 137 | 65.2 | 66.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 5 | 2.4 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 9 | 4.3 | 4.4 |
| A_little_bit | 6 | 2.9 | 3.0 |
| Somewhat | 33 | 15.7 | 16.3 |
| Quite_a_bit | 23 | 11.0 | 11.3 |
| Very_much | 131 | 62.4 | 64.5 |
| Scantron_Error | 1 | 0.5 | 0.5 |
| NA | 7 | 3.3 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 11 | 3.5 | 3.7 |
| A_little_bit | 8 | 2.5 | 2.7 |
| Somewhat | 36 | 11.4 | 12.0 |
| Quite_a_bit | 71 | 22.5 | 23.7 |
| Very_much | 174 | 55.2 | 58.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 15 | 4.8 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 7 | 2.2 | 2.3 |
| A_little_bit | 11 | 3.5 | 3.6 |
| Somewhat | 41 | 13.0 | 13.5 |
| Quite_a_bit | 78 | 24.8 | 25.7 |
| Very_much | 166 | 52.7 | 54.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 12 | 3.8 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 31 | 9.8 | 10.3 |
| A_little_bit | 36 | 11.4 | 12.0 |
| Somewhat | 97 | 30.8 | 32.2 |
| Quite_a_bit | 56 | 17.8 | 18.6 |
| Very_much | 81 | 25.7 | 26.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 10 | 3.2 | 3.3 |
| A_little_bit | 20 | 6.3 | 6.6 |
| Somewhat | 49 | 15.6 | 16.3 |
| Quite_a_bit | 86 | 27.3 | 28.6 |
| Very_much | 136 | 43.2 | 45.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 14 | 4.4 | 4.7 |
| A_little_bit | 9 | 2.9 | 3.0 |
| Somewhat | 44 | 14.0 | 14.6 |
| Quite_a_bit | 49 | 15.6 | 16.3 |
| Very_much | 185 | 58.7 | 61.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 14 | 4.4 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 23 | 7.3 | 7.8 |
| A_little_bit | 15 | 4.8 | 5.1 |
| Somewhat | 41 | 13.0 | 13.9 |
| Quite_a_bit | 47 | 14.9 | 16.0 |
| Very_much | 168 | 53.3 | 57.1 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 6.7 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 12 | 3.4 | 3.5 |
| A_little_bit | 14 | 3.9 | 4.1 |
| Somewhat | 48 | 13.5 | 14.2 |
| Quite_a_bit | 83 | 23.3 | 24.5 |
| Very_much | 182 | 51.1 | 53.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 10 | 2.8 | 2.9 |
| A_little_bit | 15 | 4.2 | 4.4 |
| Somewhat | 52 | 14.6 | 15.3 |
| Quite_a_bit | 76 | 21.3 | 22.4 |
| Very_much | 186 | 52.2 | 54.9 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 37 | 10.4 | 10.9 |
| A_little_bit | 50 | 14.0 | 14.7 |
| Somewhat | 106 | 29.8 | 31.2 |
| Quite_a_bit | 59 | 16.6 | 17.4 |
| Very_much | 86 | 24.2 | 25.3 |
| Scantron_Error | 2 | 0.6 | 0.6 |
| NA | 16 | 4.5 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 9 | 2.5 | 2.7 |
| A_little_bit | 16 | 4.5 | 4.7 |
| Somewhat | 56 | 15.7 | 16.6 |
| Quite_a_bit | 89 | 25.0 | 26.3 |
| Very_much | 167 | 46.9 | 49.4 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 18 | 5.1 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 11 | 3.1 | 3.2 |
| A_little_bit | 15 | 4.2 | 4.4 |
| Somewhat | 47 | 13.2 | 13.9 |
| Quite_a_bit | 61 | 17.1 | 18.0 |
| Very_much | 205 | 57.6 | 60.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 18 | 5.1 | 5.4 |
| A_little_bit | 16 | 4.5 | 4.8 |
| Somewhat | 59 | 16.6 | 17.6 |
| Quite_a_bit | 50 | 14.0 | 14.9 |
| Very_much | 192 | 53.9 | 57.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 21 | 5.9 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 20 | 3.4 | 3.6 |
| A_little_bit | 30 | 5.1 | 5.4 |
| Somewhat | 66 | 11.3 | 11.9 |
| Quite_a_bit | 144 | 24.6 | 25.9 |
| Very_much | 295 | 50.4 | 53.1 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 29 | 5.0 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 13 | 2.2 | 2.3 |
| A_little_bit | 34 | 5.8 | 6.1 |
| Somewhat | 54 | 9.2 | 9.7 |
| Quite_a_bit | 126 | 21.5 | 22.6 |
| Very_much | 330 | 56.4 | 59.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 28 | 4.8 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 68 | 11.6 | 12.2 |
| A_little_bit | 60 | 10.3 | 10.8 |
| Somewhat | 168 | 28.7 | 30.2 |
| Quite_a_bit | 103 | 17.6 | 18.5 |
| Very_much | 156 | 26.7 | 28.1 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 29 | 5.0 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 15 | 2.6 | 2.7 |
| A_little_bit | 19 | 3.2 | 3.4 |
| Somewhat | 91 | 15.6 | 16.4 |
| Quite_a_bit | 128 | 21.9 | 23.1 |
| Very_much | 301 | 51.5 | 54.2 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 30 | 5.1 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 19 | 3.2 | 3.4 |
| A_little_bit | 20 | 3.4 | 3.6 |
| Somewhat | 62 | 10.6 | 11.2 |
| Quite_a_bit | 84 | 14.4 | 15.1 |
| Very_much | 370 | 63.2 | 66.5 |
| Scantron_Error | 1 | 0.2 | 0.2 |
| NA | 29 | 5.0 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 28 | 4.8 | 5.1 |
| A_little_bit | 20 | 3.4 | 3.6 |
| Somewhat | 75 | 12.8 | 13.6 |
| Quite_a_bit | 58 | 9.9 | 10.5 |
| Very_much | 370 | 63.2 | 67.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 34 | 5.8 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 52 | 3.0 | 3.1 |
| A_little_bit | 53 | 3.0 | 3.2 |
| Somewhat | 195 | 11.1 | 11.7 |
| Quite_a_bit | 415 | 23.7 | 24.9 |
| Very_much | 945 | 53.9 | 56.8 |
| Scantron_Error | 5 | 0.3 | 0.3 |
| NA | 89 | 5.1 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 40 | 2.3 | 2.4 |
| A_little_bit | 58 | 3.3 | 3.5 |
| Somewhat | 190 | 10.8 | 11.4 |
| Quite_a_bit | 406 | 23.1 | 24.3 |
| Very_much | 973 | 55.5 | 58.2 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 83 | 4.7 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 149 | 8.5 | 8.9 |
| A_little_bit | 180 | 10.3 | 10.8 |
| Somewhat | 574 | 32.7 | 34.5 |
| Quite_a_bit | 334 | 19.0 | 20.0 |
| Very_much | 420 | 23.9 | 25.2 |
| Scantron_Error | 9 | 0.5 | 0.5 |
| NA | 88 | 5.0 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 38 | 2.2 | 2.3 |
| A_little_bit | 69 | 3.9 | 4.1 |
| Somewhat | 246 | 14.0 | 14.7 |
| Quite_a_bit | 399 | 22.7 | 23.9 |
| Very_much | 912 | 52.0 | 54.6 |
| Scantron_Error | 5 | 0.3 | 0.3 |
| NA | 85 | 4.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 72 | 4.1 | 4.3 |
| A_little_bit | 63 | 3.6 | 3.8 |
| Somewhat | 192 | 10.9 | 11.5 |
| Quite_a_bit | 230 | 13.1 | 13.8 |
| Very_much | 1107 | 63.1 | 66.4 |
| Scantron_Error | 4 | 0.2 | 0.2 |
| NA | 86 | 4.9 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 99 | 5.6 | 6.0 |
| A_little_bit | 57 | 3.2 | 3.4 |
| Somewhat | 224 | 12.8 | 13.5 |
| Quite_a_bit | 212 | 12.1 | 12.8 |
| Very_much | 1064 | 60.7 | 64.1 |
| Scantron_Error | 3 | 0.2 | 0.2 |
| NA | 95 | 5.4 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e11a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "a. I had all the information I needed when a treatment was chosen for my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 2 | 12.5 | 12.5 |
| A_little_bit | 0 | 0.0 | 0.0 |
| Somewhat | 1 | 6.2 | 6.2 |
| Quite_a_bit | 7 | 43.8 | 43.8 |
| Very_much | 6 | 37.5 | 37.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "b. My doctors told me the whole story about the effects of treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 1 | 6.2 | 6.2 |
| A_little_bit | 0 | 0.0 | 0.0 |
| Somewhat | 3 | 18.8 | 18.8 |
| Quite_a_bit | 4 | 25.0 | 25.0 |
| Very_much | 8 | 50.0 | 50.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "c. I knew the right questions to ask my doctor")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 3 | 18.8 | 18.8 |
| A_little_bit | 2 | 12.5 | 12.5 |
| Somewhat | 5 | 31.2 | 31.2 |
| Quite_a_bit | 3 | 18.8 | 18.8 |
| Very_much | 3 | 18.8 | 18.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11d,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "d. I had enough time to make a decision about my treatment")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 2 | 12.5 | 13.3 |
| A_little_bit | 1 | 6.2 | 6.7 |
| Somewhat | 2 | 12.5 | 13.3 |
| Quite_a_bit | 3 | 18.8 | 20.0 |
| Very_much | 7 | 43.8 | 46.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11e,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e. I am satisfied with the choices I made in treating my prostate cancer")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 1 | 6.2 | 6.2 |
| A_little_bit | 0 | 0.0 | 0.0 |
| Somewhat | 1 | 6.2 | 6.2 |
| Quite_a_bit | 5 | 31.2 | 31.2 |
| Very_much | 9 | 56.2 | 56.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$e11f,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f. I would recommend the treatment I had to a close relative or friend")
| n | % | val% | |
|---|---|---|---|
| Not_at_all | 1 | 6.2 | 6.2 |
| A_little_bit | 1 | 6.2 | 6.2 |
| Somewhat | 0 | 0.0 | 0.0 |
| Quite_a_bit | 7 | 43.8 | 43.8 |
| Very_much | 7 | 43.8 | 43.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
e12 <- as.factor(d[,"e12"])
levels(e12) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
e12 <- ordered(e12, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e12)
new.d <- apply_labels(new.d, e12 = "received instructions")
temp.d <- data.frame (new.d, e12)
result<-questionr::freq(temp.d$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 940 | 26.4 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2617 | 73.6 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 74 | 23.1 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 247 | 76.9 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 45 | 21.4 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 165 | 78.6 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 84 | 26.7 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 231 | 73.3 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 112 | 31.5 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 244 | 68.5 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 157 | 26.8 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 428 | 73.2 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 463 | 26.4 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1291 | 73.6 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e12,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e12")
| n | % | val% | |
|---|---|---|---|
| No | 5 | 31.2 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 11 | 68.8 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e13 <- as.factor(d[,"e13"])
levels(e13) <- list(None="0",
One="1",
Two="2",
Three="3",
Four_more="4",
Dont_know="88",
Scantron_Error="*")
e13 <- ordered(e13, c("None","One","Two","Three","Four_more","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e13)
new.d <- apply_labels(new.d, e13 = "times of PSA blood test")
temp.d <- data.frame (new.d, e13)
result<-questionr::freq(temp.d$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 658 | 18.5 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2899 | 81.5 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 75 | 23.4 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 246 | 76.6 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0 | 0 |
| One | 40 | 19 | 100 |
| Two | 0 | 0 | 0 |
| Three | 0 | 0 | 0 |
| Four_more | 0 | 0 | 0 |
| Dont_know | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 170 | 81 | NA |
| Total | 210 | 100 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 57 | 18.1 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 258 | 81.9 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 59 | 16.6 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 297 | 83.4 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 112 | 19.1 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 473 | 80.9 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0.0 | 0 |
| One | 311 | 17.7 | 100 |
| Two | 0 | 0.0 | 0 |
| Three | 0 | 0.0 | 0 |
| Four_more | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1443 | 82.3 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e13,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e13")
| n | % | val% | |
|---|---|---|---|
| None | 0 | 0 | 0 |
| One | 4 | 25 | 100 |
| Two | 0 | 0 | 0 |
| Three | 0 | 0 | 0 |
| Four_more | 0 | 0 | 0 |
| Dont_know | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 12 | 75 | NA |
| Total | 16 | 100 | 100 |
rm(temp.dd)
e14 <- as.factor(d[,"e14"])
levels(e14) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
e14 <- ordered(e14, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e14)
new.d <- apply_labels(new.d, e14 = "been told PSA was rising")
temp.d <- data.frame (new.d, e14)
result<-questionr::freq(temp.d$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 68 | 1.9 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3489 | 98.1 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 5 | 1.6 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 316 | 98.4 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 2 | 1 | 100 |
| Yes | 0 | 0 | 0 |
| Dont_know | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 208 | 99 | NA |
| Total | 210 | 100 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 7 | 2.2 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 308 | 97.8 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 7 | 2 | 100 |
| Yes | 0 | 0 | 0 |
| Dont_know | 0 | 0 | 0 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 349 | 98 | NA |
| Total | 356 | 100 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 14 | 2.4 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 571 | 97.6 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 31 | 1.8 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1723 | 98.2 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e14,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e14")
| n | % | val% | |
|---|---|---|---|
| No | 2 | 12.5 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 14 | 87.5 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
e15 <- as.factor(d[,"e15"])
levels(e15) <- list(No="1",
Yes="2",
Dont_know="88",
Scantron_Error="*")
e15 <- ordered(e15, c("No","Yes","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, e15)
new.d <- apply_labels(new.d, e15 = "been told recurred progressed")
temp.d <- data.frame (new.d, e15)
result<-questionr::freq(temp.d$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 147 | 4.1 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3410 | 95.9 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 5 | 1.6 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 316 | 98.4 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 6 | 2.9 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 204 | 97.1 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 16 | 5.1 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 299 | 94.9 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 27 | 7.6 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 329 | 92.4 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 13 | 2.2 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 572 | 97.8 | NA |
| Total | 585 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 79 | 4.5 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1675 | 95.5 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$e15,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "e15")
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 100 |
| Yes | 0 | 0.0 | 0 |
| Dont_know | 0 | 0.0 | 0 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
rm(temp.dd)
f1cm <- d[,"f1cm"]
new.d <- data.frame(new.d, f1cm)
new.d <- apply_labels(new.d, f1cm = "height in cm")
temp.d <- data.frame (new.d, f1cm)
result<-questionr::freq(temp.d$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How tall are you? (cm)")
| n | % | val% | |
|---|---|---|---|
| 0 | 6 | 0.2 | 0.2 |
| 0 9 | 1 | 0.0 | 0.0 |
| 1 | 9 | 0.3 | 0.3 |
| 10 | 4 | 0.1 | 0.1 |
| 11 | 4 | 0.1 | 0.1 |
| 111 | 1 | 0.0 | 0.0 |
| 12 | 1 | 0.0 | 0.0 |
| 135 | 1 | 0.0 | 0.0 |
| 148 | 1 | 0.0 | 0.0 |
| 152 | 1 | 0.0 | 0.0 |
| 164 | 1 | 0.0 | 0.0 |
| 165 | 1 | 0.0 | 0.0 |
| 170 | 1 | 0.0 | 0.0 |
| 173 | 1 | 0.0 | 0.0 |
| 175 | 1 | 0.0 | 0.0 |
| 178 | 2 | 0.1 | 0.1 |
| 180 | 1 | 0.0 | 0.0 |
| 181 | 1 | 0.0 | 0.0 |
| 185 | 2 | 0.1 | 0.1 |
| 190 | 3 | 0.1 | 0.1 |
| 2 | 5 | 0.1 | 0.1 |
| 225 | 1 | 0.0 | 0.0 |
| 228 | 1 | 0.0 | 0.0 |
| 234 | 1 | 0.0 | 0.0 |
| 245 | 1 | 0.0 | 0.0 |
| 247 | 1 | 0.0 | 0.0 |
| 255 | 1 | 0.0 | 0.0 |
| 265 | 1 | 0.0 | 0.0 |
| 280 | 1 | 0.0 | 0.0 |
| 290 | 1 | 0.0 | 0.0 |
| 3 | 1 | 0.0 | 0.0 |
| 44 | 1 | 0.0 | 0.0 |
| 47 | 1 | 0.0 | 0.0 |
| 5 | 4 | 0.1 | 0.1 |
| 6 | 2 | 0.1 | 0.1 |
| 7 | 3 | 0.1 | 0.1 |
| 72 | 1 | 0.0 | 0.0 |
| 78 | 1 | 0.0 | 0.0 |
| 8 | 2 | 0.1 | 0.1 |
| 9 | 5 | 0.1 | 0.1 |
| “NA” | 3479 | 97.8 | 97.8 |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.3 | 0.3 |
| 3 | 1 | 0.3 | 0.3 |
| “NA” | 319 | 99.4 | 99.4 |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 185 | 1 | 0.5 | 0.5 |
| 8 | 1 | 0.5 | 0.5 |
| “NA” | 208 | 99.0 | 99.0 |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 11 | 1 | 0.3 | 0.3 |
| 178 | 1 | 0.3 | 0.3 |
| “NA” | 313 | 99.4 | 99.4 |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 111 | 1 | 0.3 | 0.3 |
| 148 | 1 | 0.3 | 0.3 |
| 2 | 1 | 0.3 | 0.3 |
| 225 | 1 | 0.3 | 0.3 |
| 5 | 1 | 0.3 | 0.3 |
| 7 | 1 | 0.3 | 0.3 |
| 9 | 1 | 0.3 | 0.3 |
| “NA” | 349 | 98.0 | 98.0 |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.2 | 0.2 |
| 1 | 2 | 0.3 | 0.3 |
| 10 | 1 | 0.2 | 0.2 |
| 152 | 1 | 0.2 | 0.2 |
| 164 | 1 | 0.2 | 0.2 |
| 165 | 1 | 0.2 | 0.2 |
| 185 | 1 | 0.2 | 0.2 |
| 2 | 1 | 0.2 | 0.2 |
| 255 | 1 | 0.2 | 0.2 |
| 290 | 1 | 0.2 | 0.2 |
| 5 | 1 | 0.2 | 0.2 |
| 78 | 1 | 0.2 | 0.2 |
| “NA” | 572 | 97.8 | 97.8 |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 0.3 | 0.3 |
| 0 9 | 1 | 0.1 | 0.1 |
| 1 | 6 | 0.3 | 0.3 |
| 10 | 3 | 0.2 | 0.2 |
| 11 | 3 | 0.2 | 0.2 |
| 12 | 1 | 0.1 | 0.1 |
| 135 | 1 | 0.1 | 0.1 |
| 170 | 1 | 0.1 | 0.1 |
| 173 | 1 | 0.1 | 0.1 |
| 175 | 1 | 0.1 | 0.1 |
| 178 | 1 | 0.1 | 0.1 |
| 180 | 1 | 0.1 | 0.1 |
| 181 | 1 | 0.1 | 0.1 |
| 190 | 3 | 0.2 | 0.2 |
| 2 | 3 | 0.2 | 0.2 |
| 228 | 1 | 0.1 | 0.1 |
| 234 | 1 | 0.1 | 0.1 |
| 245 | 1 | 0.1 | 0.1 |
| 247 | 1 | 0.1 | 0.1 |
| 265 | 1 | 0.1 | 0.1 |
| 280 | 1 | 0.1 | 0.1 |
| 44 | 1 | 0.1 | 0.1 |
| 47 | 1 | 0.1 | 0.1 |
| 5 | 2 | 0.1 | 0.1 |
| 6 | 2 | 0.1 | 0.1 |
| 7 | 2 | 0.1 | 0.1 |
| 72 | 1 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| 9 | 4 | 0.2 | 0.2 |
| “NA” | 1702 | 97.0 | 97.0 |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f1cm,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f1cm")
| n | % | val% | |
|---|---|---|---|
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
rm(temp.dd)
f2lbs <- d[,"f2lbs"]
new.d <- data.frame(new.d, f2lbs)
new.d <- apply_labels(new.d, f2lbs = "weight in lbs")
temp.d <- data.frame (new.d, f2lbs)
result<-questionr::freq(temp.d$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (lbs)")
| n | % | val% | |
|---|---|---|---|
| * | 2 | 0.1 | 0.1 |
| * 3 | 1 | 0.0 | 0.0 |
| * 4 | 1 | 0.0 | 0.0 |
| * 5 | 1 | 0.0 | 0.0 |
| * 9 | 1 | 0.0 | 0.0 |
| *0 | 2 | 0.1 | 0.1 |
| *2 | 1 | 0.0 | 0.0 |
| *35 | 1 | 0.0 | 0.0 |
| *4 | 2 | 0.1 | 0.1 |
| *5 | 2 | 0.1 | 0.1 |
| *99 | 1 | 0.0 | 0.0 |
| 0 | 2 | 0.1 | 0.1 |
| 0* | 1 | 0.0 | 0.0 |
| 1 | 8 | 0.2 | 0.2 |
| 1 * | 3 | 0.1 | 0.1 |
| 1 8 | 1 | 0.0 | 0.0 |
| 1* | 3 | 0.1 | 0.1 |
| 106 | 1 | 0.0 | 0.0 |
| 110 | 2 | 0.1 | 0.1 |
| 111 | 1 | 0.0 | 0.0 |
| 112 | 1 | 0.0 | 0.0 |
| 114 | 1 | 0.0 | 0.0 |
| 115 | 3 | 0.1 | 0.1 |
| 117 | 1 | 0.0 | 0.0 |
| 119 | 1 | 0.0 | 0.0 |
| 12 | 1 | 0.0 | 0.0 |
| 120 | 6 | 0.2 | 0.2 |
| 121 | 1 | 0.0 | 0.0 |
| 122 | 1 | 0.0 | 0.0 |
| 124 | 1 | 0.0 | 0.0 |
| 125 | 5 | 0.1 | 0.1 |
| 126 | 1 | 0.0 | 0.0 |
| 127 | 3 | 0.1 | 0.1 |
| 130 | 14 | 0.4 | 0.4 |
| 132 | 1 | 0.0 | 0.0 |
| 133 | 1 | 0.0 | 0.0 |
| 134 | 1 | 0.0 | 0.0 |
| 135 | 9 | 0.3 | 0.3 |
| 137 | 7 | 0.2 | 0.2 |
| 138 | 6 | 0.2 | 0.2 |
| 139 | 4 | 0.1 | 0.1 |
| 14* | 1 | 0.0 | 0.0 |
| 140 | 20 | 0.6 | 0.6 |
| 141 | 3 | 0.1 | 0.1 |
| 142 | 5 | 0.1 | 0.1 |
| 143 | 2 | 0.1 | 0.1 |
| 144 | 1 | 0.0 | 0.0 |
| 145 | 15 | 0.4 | 0.4 |
| 146 | 4 | 0.1 | 0.1 |
| 147 | 8 | 0.2 | 0.2 |
| 148 | 8 | 0.2 | 0.2 |
| 149 | 2 | 0.1 | 0.1 |
| 150 | 40 | 1.1 | 1.1 |
| 151 | 1 | 0.0 | 0.0 |
| 152 | 8 | 0.2 | 0.2 |
| 153 | 7 | 0.2 | 0.2 |
| 154 | 10 | 0.3 | 0.3 |
| 155 | 35 | 1.0 | 1.0 |
| 156 | 11 | 0.3 | 0.3 |
| 157 | 8 | 0.2 | 0.2 |
| 158 | 15 | 0.4 | 0.4 |
| 159 | 7 | 0.2 | 0.2 |
| 160 | 57 | 1.6 | 1.6 |
| 161 | 7 | 0.2 | 0.2 |
| 162 | 16 | 0.4 | 0.4 |
| 163 | 12 | 0.3 | 0.3 |
| 164 | 10 | 0.3 | 0.3 |
| 165 | 50 | 1.4 | 1.4 |
| 166 | 6 | 0.2 | 0.2 |
| 167 | 21 | 0.6 | 0.6 |
| 168 | 24 | 0.7 | 0.7 |
| 169 | 12 | 0.3 | 0.3 |
| 170 | 71 | 2.0 | 2.0 |
| 171 | 9 | 0.3 | 0.3 |
| 172 | 18 | 0.5 | 0.5 |
| 173 | 18 | 0.5 | 0.5 |
| 174 | 15 | 0.4 | 0.4 |
| 175 | 68 | 1.9 | 1.9 |
| 176 | 17 | 0.5 | 0.5 |
| 177 | 13 | 0.4 | 0.4 |
| 178 | 31 | 0.9 | 0.9 |
| 179 | 8 | 0.2 | 0.2 |
| 18 | 2 | 0.1 | 0.1 |
| 180 | 84 | 2.4 | 2.4 |
| 181 | 7 | 0.2 | 0.2 |
| 182 | 26 | 0.7 | 0.7 |
| 183 | 20 | 0.6 | 0.6 |
| 184 | 18 | 0.5 | 0.5 |
| 185 | 85 | 2.4 | 2.4 |
| 186 | 16 | 0.4 | 0.4 |
| 187 | 23 | 0.6 | 0.6 |
| 188 | 31 | 0.9 | 0.9 |
| 189 | 28 | 0.8 | 0.8 |
| 190 | 98 | 2.8 | 2.8 |
| 191 | 9 | 0.3 | 0.3 |
| 192 | 24 | 0.7 | 0.7 |
| 193 | 21 | 0.6 | 0.6 |
| 194 | 12 | 0.3 | 0.3 |
| 195 | 66 | 1.9 | 1.9 |
| 196 | 17 | 0.5 | 0.5 |
| 197 | 25 | 0.7 | 0.7 |
| 198 | 38 | 1.1 | 1.1 |
| 199 | 18 | 0.5 | 0.5 |
| 2 | 10 | 0.3 | 0.3 |
| 2 * | 1 | 0.0 | 0.0 |
| 2 1 | 1 | 0.0 | 0.0 |
| 2 2 | 1 | 0.0 | 0.0 |
| 2 6 | 1 | 0.0 | 0.0 |
| 2* | 5 | 0.1 | 0.1 |
| 200 | 94 | 2.6 | 2.6 |
| 201 | 3 | 0.1 | 0.1 |
| 202 | 19 | 0.5 | 0.5 |
| 203 | 12 | 0.3 | 0.3 |
| 204 | 21 | 0.6 | 0.6 |
| 205 | 77 | 2.2 | 2.2 |
| 206 | 14 | 0.4 | 0.4 |
| 207 | 22 | 0.6 | 0.6 |
| 208 | 22 | 0.6 | 0.6 |
| 209 | 15 | 0.4 | 0.4 |
| 210 | 99 | 2.8 | 2.8 |
| 211 | 8 | 0.2 | 0.2 |
| 212 | 32 | 0.9 | 0.9 |
| 213 | 5 | 0.1 | 0.1 |
| 214 | 28 | 0.8 | 0.8 |
| 215 | 97 | 2.7 | 2.7 |
| 216 | 6 | 0.2 | 0.2 |
| 217 | 9 | 0.3 | 0.3 |
| 218 | 28 | 0.8 | 0.8 |
| 219 | 8 | 0.2 | 0.2 |
| 220 | 89 | 2.5 | 2.5 |
| 221 | 10 | 0.3 | 0.3 |
| 222 | 16 | 0.4 | 0.4 |
| 223 | 16 | 0.4 | 0.4 |
| 224 | 15 | 0.4 | 0.4 |
| 225 | 52 | 1.5 | 1.5 |
| 226 | 7 | 0.2 | 0.2 |
| 227 | 7 | 0.2 | 0.2 |
| 228 | 11 | 0.3 | 0.3 |
| 229 | 10 | 0.3 | 0.3 |
| 23 | 1 | 0.0 | 0.0 |
| 230 | 72 | 2.0 | 2.0 |
| 231 | 2 | 0.1 | 0.1 |
| 232 | 12 | 0.3 | 0.3 |
| 233 | 12 | 0.3 | 0.3 |
| 234 | 14 | 0.4 | 0.4 |
| 235 | 41 | 1.2 | 1.2 |
| 236 | 6 | 0.2 | 0.2 |
| 237 | 12 | 0.3 | 0.3 |
| 238 | 8 | 0.2 | 0.2 |
| 239 | 3 | 0.1 | 0.1 |
| 240 | 58 | 1.6 | 1.6 |
| 241 | 2 | 0.1 | 0.1 |
| 242 | 17 | 0.5 | 0.5 |
| 243 | 8 | 0.2 | 0.2 |
| 244 | 5 | 0.1 | 0.1 |
| 245 | 40 | 1.1 | 1.1 |
| 246 | 10 | 0.3 | 0.3 |
| 247 | 13 | 0.4 | 0.4 |
| 248 | 6 | 0.2 | 0.2 |
| 249 | 8 | 0.2 | 0.2 |
| 250 | 54 | 1.5 | 1.5 |
| 251 | 5 | 0.1 | 0.1 |
| 252 | 9 | 0.3 | 0.3 |
| 253 | 3 | 0.1 | 0.1 |
| 254 | 12 | 0.3 | 0.3 |
| 255 | 16 | 0.4 | 0.4 |
| 256 | 2 | 0.1 | 0.1 |
| 257 | 4 | 0.1 | 0.1 |
| 258 | 4 | 0.1 | 0.1 |
| 259 | 4 | 0.1 | 0.1 |
| 260 | 42 | 1.2 | 1.2 |
| 261 | 3 | 0.1 | 0.1 |
| 262 | 12 | 0.3 | 0.3 |
| 263 | 5 | 0.1 | 0.1 |
| 264 | 5 | 0.1 | 0.1 |
| 265 | 26 | 0.7 | 0.7 |
| 266 | 5 | 0.1 | 0.1 |
| 267 | 5 | 0.1 | 0.1 |
| 268 | 3 | 0.1 | 0.1 |
| 269 | 1 | 0.0 | 0.0 |
| 270 | 28 | 0.8 | 0.8 |
| 271 | 3 | 0.1 | 0.1 |
| 272 | 4 | 0.1 | 0.1 |
| 273 | 2 | 0.1 | 0.1 |
| 274 | 3 | 0.1 | 0.1 |
| 275 | 13 | 0.4 | 0.4 |
| 276 | 4 | 0.1 | 0.1 |
| 277 | 4 | 0.1 | 0.1 |
| 278 | 3 | 0.1 | 0.1 |
| 279 | 2 | 0.1 | 0.1 |
| 280 | 19 | 0.5 | 0.5 |
| 281 | 1 | 0.0 | 0.0 |
| 282 | 1 | 0.0 | 0.0 |
| 284 | 2 | 0.1 | 0.1 |
| 285 | 9 | 0.3 | 0.3 |
| 286 | 1 | 0.0 | 0.0 |
| 287 | 3 | 0.1 | 0.1 |
| 288 | 1 | 0.0 | 0.0 |
| 289 | 6 | 0.2 | 0.2 |
| 29 | 1 | 0.0 | 0.0 |
| 290 | 9 | 0.3 | 0.3 |
| 292 | 3 | 0.1 | 0.1 |
| 294 | 2 | 0.1 | 0.1 |
| 295 | 7 | 0.2 | 0.2 |
| 296 | 1 | 0.0 | 0.0 |
| 297 | 5 | 0.1 | 0.1 |
| 298 | 5 | 0.1 | 0.1 |
| 3 | 1 | 0.0 | 0.0 |
| 300 | 15 | 0.4 | 0.4 |
| 302 | 1 | 0.0 | 0.0 |
| 303 | 1 | 0.0 | 0.0 |
| 305 | 2 | 0.1 | 0.1 |
| 307 | 2 | 0.1 | 0.1 |
| 308 | 1 | 0.0 | 0.0 |
| 309 | 1 | 0.0 | 0.0 |
| 310 | 9 | 0.3 | 0.3 |
| 311 | 1 | 0.0 | 0.0 |
| 314 | 1 | 0.0 | 0.0 |
| 315 | 4 | 0.1 | 0.1 |
| 316 | 1 | 0.0 | 0.0 |
| 317 | 2 | 0.1 | 0.1 |
| 319 | 1 | 0.0 | 0.0 |
| 320 | 6 | 0.2 | 0.2 |
| 321 | 2 | 0.1 | 0.1 |
| 324 | 2 | 0.1 | 0.1 |
| 325 | 3 | 0.1 | 0.1 |
| 326 | 1 | 0.0 | 0.0 |
| 330 | 7 | 0.2 | 0.2 |
| 334 | 1 | 0.0 | 0.0 |
| 335 | 4 | 0.1 | 0.1 |
| 340 | 3 | 0.1 | 0.1 |
| 344 | 1 | 0.0 | 0.0 |
| 350 | 3 | 0.1 | 0.1 |
| 355 | 2 | 0.1 | 0.1 |
| 358 | 1 | 0.0 | 0.0 |
| 360 | 1 | 0.0 | 0.0 |
| 361 | 1 | 0.0 | 0.0 |
| 362 | 1 | 0.0 | 0.0 |
| 365 | 1 | 0.0 | 0.0 |
| 370 | 1 | 0.0 | 0.0 |
| 375 | 1 | 0.0 | 0.0 |
| 376 | 1 | 0.0 | 0.0 |
| 397 | 1 | 0.0 | 0.0 |
| 400 | 2 | 0.1 | 0.1 |
| 410 | 1 | 0.0 | 0.0 |
| 415 | 1 | 0.0 | 0.0 |
| 416 | 1 | 0.0 | 0.0 |
| 424 | 1 | 0.0 | 0.0 |
| 430 | 1 | 0.0 | 0.0 |
| 440 | 1 | 0.0 | 0.0 |
| 50 | 1 | 0.0 | 0.0 |
| 53 | 1 | 0.0 | 0.0 |
| 60 | 1 | 0.0 | 0.0 |
| 65 | 3 | 0.1 | 0.1 |
| 68 | 2 | 0.1 | 0.1 |
| 7 | 1 | 0.0 | 0.0 |
| 71 | 1 | 0.0 | 0.0 |
| 72 | 1 | 0.0 | 0.0 |
| 74 | 1 | 0.0 | 0.0 |
| 75 | 1 | 0.0 | 0.0 |
| 76 | 1 | 0.0 | 0.0 |
| 78 | 1 | 0.0 | 0.0 |
| 80 | 2 | 0.1 | 0.1 |
| 81 | 1 | 0.0 | 0.0 |
| 84 | 1 | 0.0 | 0.0 |
| 89 | 1 | 0.0 | 0.0 |
| 90 | 2 | 0.1 | 0.1 |
| 92 | 1 | 0.0 | 0.0 |
| 97 | 1 | 0.0 | 0.0 |
| 98 | 1 | 0.0 | 0.0 |
| “NA” | 386 | 10.9 | 10.9 |
| Total | 3557 | 100.0 | 100.0 |
f2kgs <- d[,"f2kgs"]
new.d <- data.frame(new.d, f2kgs)
new.d <- apply_labels(new.d, f2kgs = "weight in lbs")
temp.d <- data.frame (new.d, f2kgs)
result<-questionr::freq(temp.d$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.0 | 0.0 |
| 0 | 10 | 0.3 | 0.3 |
| 1 | 2 | 0.1 | 0.1 |
| 1 7 | 1 | 0.0 | 0.0 |
| 10 | 1 | 0.0 | 0.0 |
| 110 | 1 | 0.0 | 0.0 |
| 111 | 2 | 0.1 | 0.1 |
| 113 | 1 | 0.0 | 0.0 |
| 137 | 1 | 0.0 | 0.0 |
| 175 | 1 | 0.0 | 0.0 |
| 2 | 4 | 0.1 | 0.1 |
| 22 | 1 | 0.0 | 0.0 |
| 3 | 1 | 0.0 | 0.0 |
| 37 | 1 | 0.0 | 0.0 |
| 45 | 1 | 0.0 | 0.0 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 3 | 0.1 | 0.1 |
| 55 | 2 | 0.1 | 0.1 |
| 6 | 1 | 0.0 | 0.0 |
| 60 | 1 | 0.0 | 0.0 |
| 61 | 1 | 0.0 | 0.0 |
| 64 | 1 | 0.0 | 0.0 |
| 65 | 1 | 0.0 | 0.0 |
| 7 | 1 | 0.0 | 0.0 |
| 75 | 1 | 0.0 | 0.0 |
| 76 | 1 | 0.0 | 0.0 |
| 8 | 1 | 0.0 | 0.0 |
| 82 | 1 | 0.0 | 0.0 |
| 85 | 1 | 0.0 | 0.0 |
| 86 | 1 | 0.0 | 0.0 |
| 88 | 1 | 0.0 | 0.0 |
| 9 | 2 | 0.1 | 0.1 |
| 90 | 1 | 0.0 | 0.0 |
| 91 | 1 | 0.0 | 0.0 |
| 92 | 1 | 0.0 | 0.0 |
| “NA” | 3504 | 98.5 | 98.5 |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| *0 | 1 | 0.3 | 0.3 |
| *99 | 1 | 0.3 | 0.3 |
| 115 | 1 | 0.3 | 0.3 |
| 120 | 1 | 0.3 | 0.3 |
| 125 | 1 | 0.3 | 0.3 |
| 130 | 1 | 0.3 | 0.3 |
| 137 | 1 | 0.3 | 0.3 |
| 138 | 1 | 0.3 | 0.3 |
| 140 | 2 | 0.6 | 0.6 |
| 145 | 2 | 0.6 | 0.6 |
| 148 | 1 | 0.3 | 0.3 |
| 150 | 4 | 1.2 | 1.2 |
| 152 | 1 | 0.3 | 0.3 |
| 155 | 2 | 0.6 | 0.6 |
| 158 | 2 | 0.6 | 0.6 |
| 160 | 10 | 3.1 | 3.1 |
| 163 | 2 | 0.6 | 0.6 |
| 164 | 1 | 0.3 | 0.3 |
| 165 | 2 | 0.6 | 0.6 |
| 166 | 1 | 0.3 | 0.3 |
| 167 | 3 | 0.9 | 0.9 |
| 168 | 3 | 0.9 | 0.9 |
| 169 | 1 | 0.3 | 0.3 |
| 170 | 7 | 2.2 | 2.2 |
| 172 | 2 | 0.6 | 0.6 |
| 173 | 4 | 1.2 | 1.2 |
| 175 | 6 | 1.9 | 1.9 |
| 176 | 2 | 0.6 | 0.6 |
| 177 | 2 | 0.6 | 0.6 |
| 178 | 4 | 1.2 | 1.2 |
| 180 | 7 | 2.2 | 2.2 |
| 181 | 1 | 0.3 | 0.3 |
| 182 | 1 | 0.3 | 0.3 |
| 183 | 3 | 0.9 | 0.9 |
| 184 | 2 | 0.6 | 0.6 |
| 185 | 6 | 1.9 | 1.9 |
| 186 | 3 | 0.9 | 0.9 |
| 187 | 2 | 0.6 | 0.6 |
| 188 | 2 | 0.6 | 0.6 |
| 189 | 1 | 0.3 | 0.3 |
| 190 | 7 | 2.2 | 2.2 |
| 191 | 2 | 0.6 | 0.6 |
| 192 | 3 | 0.9 | 0.9 |
| 193 | 1 | 0.3 | 0.3 |
| 195 | 4 | 1.2 | 1.2 |
| 196 | 1 | 0.3 | 0.3 |
| 197 | 1 | 0.3 | 0.3 |
| 198 | 3 | 0.9 | 0.9 |
| 199 | 1 | 0.3 | 0.3 |
| 2* | 1 | 0.3 | 0.3 |
| 200 | 12 | 3.7 | 3.7 |
| 202 | 2 | 0.6 | 0.6 |
| 203 | 1 | 0.3 | 0.3 |
| 204 | 1 | 0.3 | 0.3 |
| 205 | 13 | 4.0 | 4.0 |
| 206 | 2 | 0.6 | 0.6 |
| 207 | 1 | 0.3 | 0.3 |
| 208 | 2 | 0.6 | 0.6 |
| 209 | 2 | 0.6 | 0.6 |
| 210 | 14 | 4.4 | 4.4 |
| 212 | 2 | 0.6 | 0.6 |
| 214 | 3 | 0.9 | 0.9 |
| 215 | 12 | 3.7 | 3.7 |
| 216 | 1 | 0.3 | 0.3 |
| 217 | 1 | 0.3 | 0.3 |
| 218 | 3 | 0.9 | 0.9 |
| 220 | 7 | 2.2 | 2.2 |
| 221 | 1 | 0.3 | 0.3 |
| 222 | 3 | 0.9 | 0.9 |
| 223 | 3 | 0.9 | 0.9 |
| 224 | 3 | 0.9 | 0.9 |
| 225 | 8 | 2.5 | 2.5 |
| 230 | 5 | 1.6 | 1.6 |
| 233 | 1 | 0.3 | 0.3 |
| 235 | 5 | 1.6 | 1.6 |
| 236 | 1 | 0.3 | 0.3 |
| 239 | 1 | 0.3 | 0.3 |
| 240 | 4 | 1.2 | 1.2 |
| 242 | 3 | 0.9 | 0.9 |
| 244 | 1 | 0.3 | 0.3 |
| 245 | 4 | 1.2 | 1.2 |
| 247 | 2 | 0.6 | 0.6 |
| 248 | 1 | 0.3 | 0.3 |
| 249 | 3 | 0.9 | 0.9 |
| 250 | 9 | 2.8 | 2.8 |
| 252 | 1 | 0.3 | 0.3 |
| 254 | 1 | 0.3 | 0.3 |
| 255 | 2 | 0.6 | 0.6 |
| 260 | 3 | 0.9 | 0.9 |
| 262 | 2 | 0.6 | 0.6 |
| 263 | 1 | 0.3 | 0.3 |
| 264 | 1 | 0.3 | 0.3 |
| 265 | 4 | 1.2 | 1.2 |
| 270 | 6 | 1.9 | 1.9 |
| 271 | 1 | 0.3 | 0.3 |
| 274 | 2 | 0.6 | 0.6 |
| 275 | 2 | 0.6 | 0.6 |
| 276 | 1 | 0.3 | 0.3 |
| 280 | 1 | 0.3 | 0.3 |
| 285 | 2 | 0.6 | 0.6 |
| 289 | 1 | 0.3 | 0.3 |
| 298 | 1 | 0.3 | 0.3 |
| 300 | 3 | 0.9 | 0.9 |
| 310 | 3 | 0.9 | 0.9 |
| 321 | 1 | 0.3 | 0.3 |
| 324 | 1 | 0.3 | 0.3 |
| 355 | 1 | 0.3 | 0.3 |
| 68 | 1 | 0.3 | 0.3 |
| “NA” | 18 | 5.6 | 5.6 |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.3 | 0.3 |
| 137 | 1 | 0.3 | 0.3 |
| “NA” | 319 | 99.4 | 99.4 |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.5 | 0.5 |
| 1 | 1 | 0.5 | 0.5 |
| 127 | 2 | 1.0 | 1.0 |
| 140 | 2 | 1.0 | 1.0 |
| 145 | 1 | 0.5 | 0.5 |
| 150 | 4 | 1.9 | 1.9 |
| 154 | 1 | 0.5 | 0.5 |
| 160 | 2 | 1.0 | 1.0 |
| 161 | 1 | 0.5 | 0.5 |
| 164 | 1 | 0.5 | 0.5 |
| 165 | 3 | 1.4 | 1.4 |
| 167 | 1 | 0.5 | 0.5 |
| 168 | 3 | 1.4 | 1.4 |
| 169 | 2 | 1.0 | 1.0 |
| 170 | 3 | 1.4 | 1.4 |
| 171 | 1 | 0.5 | 0.5 |
| 172 | 1 | 0.5 | 0.5 |
| 173 | 1 | 0.5 | 0.5 |
| 174 | 1 | 0.5 | 0.5 |
| 175 | 4 | 1.9 | 1.9 |
| 177 | 1 | 0.5 | 0.5 |
| 178 | 1 | 0.5 | 0.5 |
| 180 | 6 | 2.9 | 2.9 |
| 182 | 1 | 0.5 | 0.5 |
| 184 | 2 | 1.0 | 1.0 |
| 185 | 1 | 0.5 | 0.5 |
| 186 | 1 | 0.5 | 0.5 |
| 187 | 2 | 1.0 | 1.0 |
| 188 | 2 | 1.0 | 1.0 |
| 189 | 2 | 1.0 | 1.0 |
| 190 | 9 | 4.3 | 4.3 |
| 192 | 2 | 1.0 | 1.0 |
| 193 | 1 | 0.5 | 0.5 |
| 194 | 1 | 0.5 | 0.5 |
| 195 | 10 | 4.8 | 4.8 |
| 196 | 1 | 0.5 | 0.5 |
| 197 | 3 | 1.4 | 1.4 |
| 198 | 2 | 1.0 | 1.0 |
| 199 | 1 | 0.5 | 0.5 |
| 2* | 2 | 1.0 | 1.0 |
| 200 | 5 | 2.4 | 2.4 |
| 204 | 1 | 0.5 | 0.5 |
| 205 | 4 | 1.9 | 1.9 |
| 207 | 1 | 0.5 | 0.5 |
| 210 | 4 | 1.9 | 1.9 |
| 211 | 1 | 0.5 | 0.5 |
| 212 | 3 | 1.4 | 1.4 |
| 214 | 2 | 1.0 | 1.0 |
| 215 | 1 | 0.5 | 0.5 |
| 216 | 1 | 0.5 | 0.5 |
| 220 | 11 | 5.2 | 5.2 |
| 221 | 1 | 0.5 | 0.5 |
| 224 | 3 | 1.4 | 1.4 |
| 225 | 3 | 1.4 | 1.4 |
| 226 | 1 | 0.5 | 0.5 |
| 228 | 1 | 0.5 | 0.5 |
| 229 | 3 | 1.4 | 1.4 |
| 23 | 1 | 0.5 | 0.5 |
| 230 | 5 | 2.4 | 2.4 |
| 233 | 1 | 0.5 | 0.5 |
| 235 | 2 | 1.0 | 1.0 |
| 237 | 2 | 1.0 | 1.0 |
| 240 | 3 | 1.4 | 1.4 |
| 243 | 2 | 1.0 | 1.0 |
| 245 | 1 | 0.5 | 0.5 |
| 247 | 1 | 0.5 | 0.5 |
| 249 | 2 | 1.0 | 1.0 |
| 250 | 1 | 0.5 | 0.5 |
| 254 | 1 | 0.5 | 0.5 |
| 255 | 3 | 1.4 | 1.4 |
| 260 | 3 | 1.4 | 1.4 |
| 262 | 1 | 0.5 | 0.5 |
| 265 | 1 | 0.5 | 0.5 |
| 266 | 1 | 0.5 | 0.5 |
| 267 | 1 | 0.5 | 0.5 |
| 268 | 1 | 0.5 | 0.5 |
| 270 | 4 | 1.9 | 1.9 |
| 272 | 1 | 0.5 | 0.5 |
| 280 | 1 | 0.5 | 0.5 |
| 285 | 1 | 0.5 | 0.5 |
| 292 | 1 | 0.5 | 0.5 |
| 310 | 1 | 0.5 | 0.5 |
| 311 | 1 | 0.5 | 0.5 |
| 315 | 1 | 0.5 | 0.5 |
| 330 | 1 | 0.5 | 0.5 |
| 340 | 1 | 0.5 | 0.5 |
| 350 | 1 | 0.5 | 0.5 |
| 416 | 1 | 0.5 | 0.5 |
| 53 | 1 | 0.5 | 0.5 |
| 65 | 1 | 0.5 | 0.5 |
| 75 | 1 | 0.5 | 0.5 |
| 90 | 1 | 0.5 | 0.5 |
| “NA” | 25 | 11.9 | 11.9 |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| 111 | 1 | 0.5 | 0.5 |
| 8 | 1 | 0.5 | 0.5 |
| 88 | 1 | 0.5 | 0.5 |
| 92 | 1 | 0.5 | 0.5 |
| “NA” | 206 | 98.1 | 98.1 |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| *5 | 1 | 0.3 | 0.3 |
| 112 | 1 | 0.3 | 0.3 |
| 114 | 1 | 0.3 | 0.3 |
| 125 | 1 | 0.3 | 0.3 |
| 138 | 1 | 0.3 | 0.3 |
| 140 | 1 | 0.3 | 0.3 |
| 145 | 2 | 0.6 | 0.6 |
| 146 | 1 | 0.3 | 0.3 |
| 148 | 1 | 0.3 | 0.3 |
| 150 | 4 | 1.3 | 1.3 |
| 152 | 1 | 0.3 | 0.3 |
| 153 | 1 | 0.3 | 0.3 |
| 154 | 1 | 0.3 | 0.3 |
| 155 | 3 | 1.0 | 1.0 |
| 156 | 1 | 0.3 | 0.3 |
| 157 | 2 | 0.6 | 0.6 |
| 158 | 1 | 0.3 | 0.3 |
| 159 | 1 | 0.3 | 0.3 |
| 160 | 4 | 1.3 | 1.3 |
| 162 | 3 | 1.0 | 1.0 |
| 163 | 1 | 0.3 | 0.3 |
| 165 | 6 | 1.9 | 1.9 |
| 167 | 5 | 1.6 | 1.6 |
| 168 | 1 | 0.3 | 0.3 |
| 170 | 5 | 1.6 | 1.6 |
| 172 | 2 | 0.6 | 0.6 |
| 173 | 2 | 0.6 | 0.6 |
| 174 | 1 | 0.3 | 0.3 |
| 175 | 7 | 2.2 | 2.2 |
| 176 | 1 | 0.3 | 0.3 |
| 177 | 3 | 1.0 | 1.0 |
| 178 | 5 | 1.6 | 1.6 |
| 179 | 1 | 0.3 | 0.3 |
| 180 | 10 | 3.2 | 3.2 |
| 182 | 5 | 1.6 | 1.6 |
| 184 | 4 | 1.3 | 1.3 |
| 185 | 10 | 3.2 | 3.2 |
| 187 | 2 | 0.6 | 0.6 |
| 188 | 1 | 0.3 | 0.3 |
| 189 | 5 | 1.6 | 1.6 |
| 190 | 8 | 2.5 | 2.5 |
| 192 | 2 | 0.6 | 0.6 |
| 193 | 2 | 0.6 | 0.6 |
| 195 | 9 | 2.9 | 2.9 |
| 196 | 2 | 0.6 | 0.6 |
| 197 | 1 | 0.3 | 0.3 |
| 198 | 1 | 0.3 | 0.3 |
| 199 | 3 | 1.0 | 1.0 |
| 2 | 1 | 0.3 | 0.3 |
| 2 * | 1 | 0.3 | 0.3 |
| 2 2 | 1 | 0.3 | 0.3 |
| 200 | 10 | 3.2 | 3.2 |
| 202 | 3 | 1.0 | 1.0 |
| 205 | 6 | 1.9 | 1.9 |
| 206 | 1 | 0.3 | 0.3 |
| 207 | 3 | 1.0 | 1.0 |
| 208 | 5 | 1.6 | 1.6 |
| 209 | 3 | 1.0 | 1.0 |
| 210 | 10 | 3.2 | 3.2 |
| 211 | 1 | 0.3 | 0.3 |
| 212 | 1 | 0.3 | 0.3 |
| 214 | 2 | 0.6 | 0.6 |
| 215 | 9 | 2.9 | 2.9 |
| 219 | 2 | 0.6 | 0.6 |
| 220 | 9 | 2.9 | 2.9 |
| 222 | 2 | 0.6 | 0.6 |
| 223 | 1 | 0.3 | 0.3 |
| 225 | 1 | 0.3 | 0.3 |
| 226 | 3 | 1.0 | 1.0 |
| 228 | 1 | 0.3 | 0.3 |
| 230 | 3 | 1.0 | 1.0 |
| 232 | 2 | 0.6 | 0.6 |
| 233 | 1 | 0.3 | 0.3 |
| 234 | 1 | 0.3 | 0.3 |
| 235 | 3 | 1.0 | 1.0 |
| 237 | 1 | 0.3 | 0.3 |
| 238 | 2 | 0.6 | 0.6 |
| 239 | 1 | 0.3 | 0.3 |
| 240 | 6 | 1.9 | 1.9 |
| 242 | 2 | 0.6 | 0.6 |
| 243 | 1 | 0.3 | 0.3 |
| 244 | 1 | 0.3 | 0.3 |
| 245 | 4 | 1.3 | 1.3 |
| 249 | 1 | 0.3 | 0.3 |
| 250 | 3 | 1.0 | 1.0 |
| 251 | 1 | 0.3 | 0.3 |
| 252 | 1 | 0.3 | 0.3 |
| 254 | 2 | 0.6 | 0.6 |
| 260 | 2 | 0.6 | 0.6 |
| 261 | 1 | 0.3 | 0.3 |
| 262 | 2 | 0.6 | 0.6 |
| 263 | 1 | 0.3 | 0.3 |
| 265 | 6 | 1.9 | 1.9 |
| 270 | 1 | 0.3 | 0.3 |
| 273 | 1 | 0.3 | 0.3 |
| 275 | 3 | 1.0 | 1.0 |
| 280 | 2 | 0.6 | 0.6 |
| 285 | 1 | 0.3 | 0.3 |
| 287 | 1 | 0.3 | 0.3 |
| 289 | 1 | 0.3 | 0.3 |
| 290 | 2 | 0.6 | 0.6 |
| 294 | 1 | 0.3 | 0.3 |
| 300 | 1 | 0.3 | 0.3 |
| 305 | 1 | 0.3 | 0.3 |
| 308 | 1 | 0.3 | 0.3 |
| 325 | 1 | 0.3 | 0.3 |
| 355 | 1 | 0.3 | 0.3 |
| 440 | 1 | 0.3 | 0.3 |
| 65 | 1 | 0.3 | 0.3 |
| 81 | 1 | 0.3 | 0.3 |
| “NA” | 33 | 10.5 | 10.5 |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| 0 | 2 | 0.6 | 0.6 |
| 2 | 1 | 0.3 | 0.3 |
| 75 | 1 | 0.3 | 0.3 |
| “NA” | 311 | 98.7 | 98.7 |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| *0 | 1 | 0.3 | 0.3 |
| *2 | 1 | 0.3 | 0.3 |
| *4 | 1 | 0.3 | 0.3 |
| 0* | 1 | 0.3 | 0.3 |
| 1 | 2 | 0.6 | 0.6 |
| 1* | 1 | 0.3 | 0.3 |
| 115 | 2 | 0.6 | 0.6 |
| 120 | 1 | 0.3 | 0.3 |
| 130 | 4 | 1.1 | 1.1 |
| 135 | 2 | 0.6 | 0.6 |
| 137 | 2 | 0.6 | 0.6 |
| 138 | 1 | 0.3 | 0.3 |
| 139 | 1 | 0.3 | 0.3 |
| 140 | 3 | 0.8 | 0.8 |
| 141 | 1 | 0.3 | 0.3 |
| 143 | 1 | 0.3 | 0.3 |
| 145 | 2 | 0.6 | 0.6 |
| 146 | 1 | 0.3 | 0.3 |
| 147 | 2 | 0.6 | 0.6 |
| 150 | 1 | 0.3 | 0.3 |
| 152 | 1 | 0.3 | 0.3 |
| 153 | 3 | 0.8 | 0.8 |
| 154 | 1 | 0.3 | 0.3 |
| 155 | 6 | 1.7 | 1.7 |
| 156 | 1 | 0.3 | 0.3 |
| 157 | 2 | 0.6 | 0.6 |
| 158 | 2 | 0.6 | 0.6 |
| 159 | 1 | 0.3 | 0.3 |
| 160 | 6 | 1.7 | 1.7 |
| 161 | 1 | 0.3 | 0.3 |
| 162 | 1 | 0.3 | 0.3 |
| 163 | 1 | 0.3 | 0.3 |
| 164 | 1 | 0.3 | 0.3 |
| 165 | 3 | 0.8 | 0.8 |
| 166 | 2 | 0.6 | 0.6 |
| 168 | 2 | 0.6 | 0.6 |
| 169 | 1 | 0.3 | 0.3 |
| 170 | 7 | 2.0 | 2.0 |
| 175 | 6 | 1.7 | 1.7 |
| 176 | 1 | 0.3 | 0.3 |
| 177 | 2 | 0.6 | 0.6 |
| 178 | 3 | 0.8 | 0.8 |
| 180 | 6 | 1.7 | 1.7 |
| 182 | 4 | 1.1 | 1.1 |
| 183 | 5 | 1.4 | 1.4 |
| 184 | 1 | 0.3 | 0.3 |
| 185 | 15 | 4.2 | 4.2 |
| 186 | 2 | 0.6 | 0.6 |
| 187 | 1 | 0.3 | 0.3 |
| 188 | 1 | 0.3 | 0.3 |
| 189 | 3 | 0.8 | 0.8 |
| 190 | 9 | 2.5 | 2.5 |
| 191 | 1 | 0.3 | 0.3 |
| 192 | 1 | 0.3 | 0.3 |
| 193 | 3 | 0.8 | 0.8 |
| 194 | 2 | 0.6 | 0.6 |
| 195 | 4 | 1.1 | 1.1 |
| 196 | 1 | 0.3 | 0.3 |
| 197 | 3 | 0.8 | 0.8 |
| 198 | 2 | 0.6 | 0.6 |
| 199 | 1 | 0.3 | 0.3 |
| 2 | 1 | 0.3 | 0.3 |
| 200 | 7 | 2.0 | 2.0 |
| 201 | 1 | 0.3 | 0.3 |
| 203 | 3 | 0.8 | 0.8 |
| 205 | 3 | 0.8 | 0.8 |
| 206 | 2 | 0.6 | 0.6 |
| 207 | 3 | 0.8 | 0.8 |
| 208 | 4 | 1.1 | 1.1 |
| 209 | 1 | 0.3 | 0.3 |
| 210 | 8 | 2.2 | 2.2 |
| 211 | 1 | 0.3 | 0.3 |
| 212 | 4 | 1.1 | 1.1 |
| 213 | 1 | 0.3 | 0.3 |
| 214 | 1 | 0.3 | 0.3 |
| 215 | 13 | 3.7 | 3.7 |
| 216 | 1 | 0.3 | 0.3 |
| 218 | 4 | 1.1 | 1.1 |
| 220 | 11 | 3.1 | 3.1 |
| 221 | 1 | 0.3 | 0.3 |
| 222 | 1 | 0.3 | 0.3 |
| 223 | 1 | 0.3 | 0.3 |
| 224 | 1 | 0.3 | 0.3 |
| 225 | 3 | 0.8 | 0.8 |
| 230 | 14 | 3.9 | 3.9 |
| 232 | 2 | 0.6 | 0.6 |
| 233 | 2 | 0.6 | 0.6 |
| 234 | 2 | 0.6 | 0.6 |
| 235 | 4 | 1.1 | 1.1 |
| 237 | 2 | 0.6 | 0.6 |
| 240 | 6 | 1.7 | 1.7 |
| 241 | 1 | 0.3 | 0.3 |
| 242 | 1 | 0.3 | 0.3 |
| 243 | 1 | 0.3 | 0.3 |
| 244 | 1 | 0.3 | 0.3 |
| 245 | 4 | 1.1 | 1.1 |
| 246 | 1 | 0.3 | 0.3 |
| 247 | 2 | 0.6 | 0.6 |
| 250 | 4 | 1.1 | 1.1 |
| 255 | 3 | 0.8 | 0.8 |
| 257 | 1 | 0.3 | 0.3 |
| 260 | 8 | 2.2 | 2.2 |
| 261 | 1 | 0.3 | 0.3 |
| 262 | 2 | 0.6 | 0.6 |
| 264 | 1 | 0.3 | 0.3 |
| 265 | 2 | 0.6 | 0.6 |
| 266 | 2 | 0.6 | 0.6 |
| 268 | 1 | 0.3 | 0.3 |
| 270 | 2 | 0.6 | 0.6 |
| 271 | 1 | 0.3 | 0.3 |
| 275 | 3 | 0.8 | 0.8 |
| 277 | 1 | 0.3 | 0.3 |
| 280 | 3 | 0.8 | 0.8 |
| 281 | 1 | 0.3 | 0.3 |
| 285 | 1 | 0.3 | 0.3 |
| 287 | 1 | 0.3 | 0.3 |
| 295 | 2 | 0.6 | 0.6 |
| 298 | 1 | 0.3 | 0.3 |
| 315 | 1 | 0.3 | 0.3 |
| 317 | 1 | 0.3 | 0.3 |
| 350 | 1 | 0.3 | 0.3 |
| 361 | 1 | 0.3 | 0.3 |
| 375 | 1 | 0.3 | 0.3 |
| 376 | 1 | 0.3 | 0.3 |
| 397 | 1 | 0.3 | 0.3 |
| 424 | 1 | 0.3 | 0.3 |
| 68 | 1 | 0.3 | 0.3 |
| 72 | 1 | 0.3 | 0.3 |
| 74 | 1 | 0.3 | 0.3 |
| 76 | 1 | 0.3 | 0.3 |
| “NA” | 34 | 9.6 | 9.6 |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| 10 | 1 | 0.3 | 0.3 |
| 2 | 1 | 0.3 | 0.3 |
| 55 | 1 | 0.3 | 0.3 |
| 61 | 1 | 0.3 | 0.3 |
| “NA” | 352 | 98.9 | 98.9 |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| *5 | 1 | 0.2 | 0.2 |
| 1 | 2 | 0.3 | 0.3 |
| 1* | 1 | 0.2 | 0.2 |
| 111 | 1 | 0.2 | 0.2 |
| 12 | 1 | 0.2 | 0.2 |
| 120 | 2 | 0.3 | 0.3 |
| 124 | 1 | 0.2 | 0.2 |
| 126 | 1 | 0.2 | 0.2 |
| 127 | 1 | 0.2 | 0.2 |
| 130 | 5 | 0.9 | 0.9 |
| 132 | 1 | 0.2 | 0.2 |
| 135 | 1 | 0.2 | 0.2 |
| 137 | 1 | 0.2 | 0.2 |
| 138 | 2 | 0.3 | 0.3 |
| 139 | 1 | 0.2 | 0.2 |
| 140 | 2 | 0.3 | 0.3 |
| 141 | 1 | 0.2 | 0.2 |
| 145 | 4 | 0.7 | 0.7 |
| 147 | 2 | 0.3 | 0.3 |
| 148 | 3 | 0.5 | 0.5 |
| 149 | 2 | 0.3 | 0.3 |
| 150 | 9 | 1.5 | 1.5 |
| 151 | 1 | 0.2 | 0.2 |
| 152 | 2 | 0.3 | 0.3 |
| 153 | 1 | 0.2 | 0.2 |
| 155 | 6 | 1.0 | 1.0 |
| 156 | 3 | 0.5 | 0.5 |
| 157 | 2 | 0.3 | 0.3 |
| 158 | 1 | 0.2 | 0.2 |
| 160 | 10 | 1.7 | 1.7 |
| 161 | 1 | 0.2 | 0.2 |
| 162 | 2 | 0.3 | 0.3 |
| 163 | 2 | 0.3 | 0.3 |
| 164 | 2 | 0.3 | 0.3 |
| 165 | 9 | 1.5 | 1.5 |
| 167 | 5 | 0.9 | 0.9 |
| 168 | 2 | 0.3 | 0.3 |
| 169 | 2 | 0.3 | 0.3 |
| 170 | 9 | 1.5 | 1.5 |
| 173 | 3 | 0.5 | 0.5 |
| 174 | 6 | 1.0 | 1.0 |
| 175 | 13 | 2.2 | 2.2 |
| 176 | 2 | 0.3 | 0.3 |
| 177 | 1 | 0.2 | 0.2 |
| 178 | 4 | 0.7 | 0.7 |
| 179 | 1 | 0.2 | 0.2 |
| 180 | 24 | 4.1 | 4.1 |
| 181 | 1 | 0.2 | 0.2 |
| 182 | 2 | 0.3 | 0.3 |
| 183 | 5 | 0.9 | 0.9 |
| 184 | 3 | 0.5 | 0.5 |
| 185 | 17 | 2.9 | 2.9 |
| 186 | 2 | 0.3 | 0.3 |
| 187 | 4 | 0.7 | 0.7 |
| 188 | 6 | 1.0 | 1.0 |
| 189 | 3 | 0.5 | 0.5 |
| 190 | 14 | 2.4 | 2.4 |
| 191 | 1 | 0.2 | 0.2 |
| 192 | 3 | 0.5 | 0.5 |
| 193 | 3 | 0.5 | 0.5 |
| 194 | 2 | 0.3 | 0.3 |
| 195 | 11 | 1.9 | 1.9 |
| 196 | 4 | 0.7 | 0.7 |
| 197 | 4 | 0.7 | 0.7 |
| 198 | 11 | 1.9 | 1.9 |
| 199 | 4 | 0.7 | 0.7 |
| 2 | 2 | 0.3 | 0.3 |
| 200 | 10 | 1.7 | 1.7 |
| 202 | 7 | 1.2 | 1.2 |
| 203 | 3 | 0.5 | 0.5 |
| 204 | 6 | 1.0 | 1.0 |
| 205 | 17 | 2.9 | 2.9 |
| 206 | 4 | 0.7 | 0.7 |
| 207 | 4 | 0.7 | 0.7 |
| 208 | 2 | 0.3 | 0.3 |
| 210 | 16 | 2.7 | 2.7 |
| 211 | 2 | 0.3 | 0.3 |
| 212 | 7 | 1.2 | 1.2 |
| 214 | 8 | 1.4 | 1.4 |
| 215 | 9 | 1.5 | 1.5 |
| 216 | 1 | 0.2 | 0.2 |
| 217 | 2 | 0.3 | 0.3 |
| 218 | 5 | 0.9 | 0.9 |
| 219 | 1 | 0.2 | 0.2 |
| 220 | 10 | 1.7 | 1.7 |
| 221 | 2 | 0.3 | 0.3 |
| 222 | 2 | 0.3 | 0.3 |
| 224 | 3 | 0.5 | 0.5 |
| 225 | 10 | 1.7 | 1.7 |
| 226 | 1 | 0.2 | 0.2 |
| 227 | 2 | 0.3 | 0.3 |
| 228 | 2 | 0.3 | 0.3 |
| 229 | 2 | 0.3 | 0.3 |
| 230 | 15 | 2.6 | 2.6 |
| 232 | 1 | 0.2 | 0.2 |
| 233 | 5 | 0.9 | 0.9 |
| 234 | 5 | 0.9 | 0.9 |
| 235 | 2 | 0.3 | 0.3 |
| 236 | 2 | 0.3 | 0.3 |
| 237 | 2 | 0.3 | 0.3 |
| 238 | 3 | 0.5 | 0.5 |
| 240 | 12 | 2.1 | 2.1 |
| 242 | 2 | 0.3 | 0.3 |
| 245 | 5 | 0.9 | 0.9 |
| 246 | 3 | 0.5 | 0.5 |
| 247 | 1 | 0.2 | 0.2 |
| 248 | 1 | 0.2 | 0.2 |
| 250 | 5 | 0.9 | 0.9 |
| 251 | 2 | 0.3 | 0.3 |
| 252 | 1 | 0.2 | 0.2 |
| 254 | 3 | 0.5 | 0.5 |
| 255 | 2 | 0.3 | 0.3 |
| 258 | 2 | 0.3 | 0.3 |
| 259 | 2 | 0.3 | 0.3 |
| 260 | 7 | 1.2 | 1.2 |
| 262 | 2 | 0.3 | 0.3 |
| 265 | 1 | 0.2 | 0.2 |
| 267 | 1 | 0.2 | 0.2 |
| 269 | 1 | 0.2 | 0.2 |
| 270 | 3 | 0.5 | 0.5 |
| 271 | 1 | 0.2 | 0.2 |
| 273 | 1 | 0.2 | 0.2 |
| 275 | 3 | 0.5 | 0.5 |
| 276 | 1 | 0.2 | 0.2 |
| 277 | 1 | 0.2 | 0.2 |
| 280 | 1 | 0.2 | 0.2 |
| 285 | 2 | 0.3 | 0.3 |
| 288 | 1 | 0.2 | 0.2 |
| 290 | 4 | 0.7 | 0.7 |
| 292 | 1 | 0.2 | 0.2 |
| 295 | 1 | 0.2 | 0.2 |
| 296 | 1 | 0.2 | 0.2 |
| 300 | 3 | 0.5 | 0.5 |
| 303 | 1 | 0.2 | 0.2 |
| 307 | 1 | 0.2 | 0.2 |
| 310 | 2 | 0.3 | 0.3 |
| 316 | 1 | 0.2 | 0.2 |
| 320 | 3 | 0.5 | 0.5 |
| 326 | 1 | 0.2 | 0.2 |
| 330 | 2 | 0.3 | 0.3 |
| 334 | 1 | 0.2 | 0.2 |
| 335 | 2 | 0.3 | 0.3 |
| 340 | 1 | 0.2 | 0.2 |
| 350 | 1 | 0.2 | 0.2 |
| 362 | 1 | 0.2 | 0.2 |
| 400 | 1 | 0.2 | 0.2 |
| 415 | 1 | 0.2 | 0.2 |
| 430 | 1 | 0.2 | 0.2 |
| 89 | 1 | 0.2 | 0.2 |
| 90 | 1 | 0.2 | 0.2 |
| “NA” | 52 | 8.9 | 8.9 |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.2 | 0.2 |
| 50 | 1 | 0.2 | 0.2 |
| 55 | 1 | 0.2 | 0.2 |
| 6 | 1 | 0.2 | 0.2 |
| 60 | 1 | 0.2 | 0.2 |
| 64 | 1 | 0.2 | 0.2 |
| 85 | 1 | 0.2 | 0.2 |
| 86 | 1 | 0.2 | 0.2 |
| 9 | 2 | 0.3 | 0.3 |
| “NA” | 575 | 98.3 | 98.3 |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| * | 1 | 0.1 | 0.1 |
| * 3 | 1 | 0.1 | 0.1 |
| * 4 | 1 | 0.1 | 0.1 |
| * 5 | 1 | 0.1 | 0.1 |
| * 9 | 1 | 0.1 | 0.1 |
| *35 | 1 | 0.1 | 0.1 |
| *4 | 1 | 0.1 | 0.1 |
| 0 | 2 | 0.1 | 0.1 |
| 1 | 3 | 0.2 | 0.2 |
| 1 * | 3 | 0.2 | 0.2 |
| 1 8 | 1 | 0.1 | 0.1 |
| 1* | 1 | 0.1 | 0.1 |
| 106 | 1 | 0.1 | 0.1 |
| 110 | 2 | 0.1 | 0.1 |
| 117 | 1 | 0.1 | 0.1 |
| 119 | 1 | 0.1 | 0.1 |
| 120 | 2 | 0.1 | 0.1 |
| 121 | 1 | 0.1 | 0.1 |
| 122 | 1 | 0.1 | 0.1 |
| 125 | 3 | 0.2 | 0.2 |
| 130 | 4 | 0.2 | 0.2 |
| 133 | 1 | 0.1 | 0.1 |
| 134 | 1 | 0.1 | 0.1 |
| 135 | 6 | 0.3 | 0.3 |
| 137 | 3 | 0.2 | 0.2 |
| 138 | 1 | 0.1 | 0.1 |
| 139 | 2 | 0.1 | 0.1 |
| 14* | 1 | 0.1 | 0.1 |
| 140 | 9 | 0.5 | 0.5 |
| 141 | 1 | 0.1 | 0.1 |
| 142 | 5 | 0.3 | 0.3 |
| 143 | 1 | 0.1 | 0.1 |
| 144 | 1 | 0.1 | 0.1 |
| 145 | 4 | 0.2 | 0.2 |
| 146 | 2 | 0.1 | 0.1 |
| 147 | 4 | 0.2 | 0.2 |
| 148 | 3 | 0.2 | 0.2 |
| 150 | 18 | 1.0 | 1.0 |
| 152 | 3 | 0.2 | 0.2 |
| 153 | 2 | 0.1 | 0.1 |
| 154 | 7 | 0.4 | 0.4 |
| 155 | 18 | 1.0 | 1.0 |
| 156 | 6 | 0.3 | 0.3 |
| 157 | 2 | 0.1 | 0.1 |
| 158 | 9 | 0.5 | 0.5 |
| 159 | 5 | 0.3 | 0.3 |
| 160 | 25 | 1.4 | 1.4 |
| 161 | 4 | 0.2 | 0.2 |
| 162 | 10 | 0.6 | 0.6 |
| 163 | 6 | 0.3 | 0.3 |
| 164 | 5 | 0.3 | 0.3 |
| 165 | 27 | 1.5 | 1.5 |
| 166 | 3 | 0.2 | 0.2 |
| 167 | 7 | 0.4 | 0.4 |
| 168 | 13 | 0.7 | 0.7 |
| 169 | 6 | 0.3 | 0.3 |
| 170 | 40 | 2.3 | 2.3 |
| 171 | 8 | 0.5 | 0.5 |
| 172 | 13 | 0.7 | 0.7 |
| 173 | 8 | 0.5 | 0.5 |
| 174 | 7 | 0.4 | 0.4 |
| 175 | 32 | 1.8 | 1.8 |
| 176 | 11 | 0.6 | 0.6 |
| 177 | 4 | 0.2 | 0.2 |
| 178 | 14 | 0.8 | 0.8 |
| 179 | 5 | 0.3 | 0.3 |
| 18 | 2 | 0.1 | 0.1 |
| 180 | 31 | 1.8 | 1.8 |
| 181 | 5 | 0.3 | 0.3 |
| 182 | 13 | 0.7 | 0.7 |
| 183 | 7 | 0.4 | 0.4 |
| 184 | 6 | 0.3 | 0.3 |
| 185 | 34 | 1.9 | 1.9 |
| 186 | 8 | 0.5 | 0.5 |
| 187 | 11 | 0.6 | 0.6 |
| 188 | 18 | 1.0 | 1.0 |
| 189 | 13 | 0.7 | 0.7 |
| 190 | 50 | 2.9 | 2.9 |
| 191 | 5 | 0.3 | 0.3 |
| 192 | 13 | 0.7 | 0.7 |
| 193 | 11 | 0.6 | 0.6 |
| 194 | 7 | 0.4 | 0.4 |
| 195 | 28 | 1.6 | 1.6 |
| 196 | 8 | 0.5 | 0.5 |
| 197 | 13 | 0.7 | 0.7 |
| 198 | 19 | 1.1 | 1.1 |
| 199 | 8 | 0.5 | 0.5 |
| 2 | 6 | 0.3 | 0.3 |
| 2 1 | 1 | 0.1 | 0.1 |
| 2 6 | 1 | 0.1 | 0.1 |
| 2* | 2 | 0.1 | 0.1 |
| 200 | 49 | 2.8 | 2.8 |
| 201 | 2 | 0.1 | 0.1 |
| 202 | 7 | 0.4 | 0.4 |
| 203 | 5 | 0.3 | 0.3 |
| 204 | 13 | 0.7 | 0.7 |
| 205 | 34 | 1.9 | 1.9 |
| 206 | 5 | 0.3 | 0.3 |
| 207 | 9 | 0.5 | 0.5 |
| 208 | 9 | 0.5 | 0.5 |
| 209 | 9 | 0.5 | 0.5 |
| 210 | 46 | 2.6 | 2.6 |
| 211 | 3 | 0.2 | 0.2 |
| 212 | 15 | 0.9 | 0.9 |
| 213 | 4 | 0.2 | 0.2 |
| 214 | 12 | 0.7 | 0.7 |
| 215 | 53 | 3.0 | 3.0 |
| 216 | 2 | 0.1 | 0.1 |
| 217 | 6 | 0.3 | 0.3 |
| 218 | 16 | 0.9 | 0.9 |
| 219 | 5 | 0.3 | 0.3 |
| 220 | 41 | 2.3 | 2.3 |
| 221 | 5 | 0.3 | 0.3 |
| 222 | 8 | 0.5 | 0.5 |
| 223 | 11 | 0.6 | 0.6 |
| 224 | 5 | 0.3 | 0.3 |
| 225 | 27 | 1.5 | 1.5 |
| 226 | 2 | 0.1 | 0.1 |
| 227 | 5 | 0.3 | 0.3 |
| 228 | 7 | 0.4 | 0.4 |
| 229 | 5 | 0.3 | 0.3 |
| 230 | 30 | 1.7 | 1.7 |
| 231 | 2 | 0.1 | 0.1 |
| 232 | 7 | 0.4 | 0.4 |
| 233 | 2 | 0.1 | 0.1 |
| 234 | 6 | 0.3 | 0.3 |
| 235 | 25 | 1.4 | 1.4 |
| 236 | 3 | 0.2 | 0.2 |
| 237 | 5 | 0.3 | 0.3 |
| 238 | 3 | 0.2 | 0.2 |
| 239 | 1 | 0.1 | 0.1 |
| 240 | 27 | 1.5 | 1.5 |
| 241 | 1 | 0.1 | 0.1 |
| 242 | 8 | 0.5 | 0.5 |
| 243 | 3 | 0.2 | 0.2 |
| 244 | 2 | 0.1 | 0.1 |
| 245 | 22 | 1.3 | 1.3 |
| 246 | 6 | 0.3 | 0.3 |
| 247 | 7 | 0.4 | 0.4 |
| 248 | 4 | 0.2 | 0.2 |
| 249 | 2 | 0.1 | 0.1 |
| 250 | 32 | 1.8 | 1.8 |
| 251 | 2 | 0.1 | 0.1 |
| 252 | 6 | 0.3 | 0.3 |
| 253 | 3 | 0.2 | 0.2 |
| 254 | 5 | 0.3 | 0.3 |
| 255 | 6 | 0.3 | 0.3 |
| 256 | 2 | 0.1 | 0.1 |
| 257 | 3 | 0.2 | 0.2 |
| 258 | 2 | 0.1 | 0.1 |
| 259 | 1 | 0.1 | 0.1 |
| 260 | 19 | 1.1 | 1.1 |
| 261 | 1 | 0.1 | 0.1 |
| 262 | 3 | 0.2 | 0.2 |
| 263 | 3 | 0.2 | 0.2 |
| 264 | 3 | 0.2 | 0.2 |
| 265 | 12 | 0.7 | 0.7 |
| 266 | 2 | 0.1 | 0.1 |
| 267 | 3 | 0.2 | 0.2 |
| 268 | 1 | 0.1 | 0.1 |
| 270 | 12 | 0.7 | 0.7 |
| 272 | 3 | 0.2 | 0.2 |
| 274 | 1 | 0.1 | 0.1 |
| 275 | 1 | 0.1 | 0.1 |
| 276 | 2 | 0.1 | 0.1 |
| 277 | 2 | 0.1 | 0.1 |
| 278 | 3 | 0.2 | 0.2 |
| 279 | 2 | 0.1 | 0.1 |
| 280 | 11 | 0.6 | 0.6 |
| 282 | 1 | 0.1 | 0.1 |
| 284 | 2 | 0.1 | 0.1 |
| 285 | 2 | 0.1 | 0.1 |
| 286 | 1 | 0.1 | 0.1 |
| 287 | 1 | 0.1 | 0.1 |
| 289 | 4 | 0.2 | 0.2 |
| 29 | 1 | 0.1 | 0.1 |
| 290 | 3 | 0.2 | 0.2 |
| 292 | 1 | 0.1 | 0.1 |
| 294 | 1 | 0.1 | 0.1 |
| 295 | 4 | 0.2 | 0.2 |
| 297 | 5 | 0.3 | 0.3 |
| 298 | 3 | 0.2 | 0.2 |
| 3 | 1 | 0.1 | 0.1 |
| 300 | 8 | 0.5 | 0.5 |
| 302 | 1 | 0.1 | 0.1 |
| 305 | 1 | 0.1 | 0.1 |
| 307 | 1 | 0.1 | 0.1 |
| 309 | 1 | 0.1 | 0.1 |
| 310 | 3 | 0.2 | 0.2 |
| 314 | 1 | 0.1 | 0.1 |
| 315 | 2 | 0.1 | 0.1 |
| 317 | 1 | 0.1 | 0.1 |
| 319 | 1 | 0.1 | 0.1 |
| 320 | 3 | 0.2 | 0.2 |
| 321 | 1 | 0.1 | 0.1 |
| 324 | 1 | 0.1 | 0.1 |
| 325 | 2 | 0.1 | 0.1 |
| 330 | 4 | 0.2 | 0.2 |
| 335 | 2 | 0.1 | 0.1 |
| 340 | 1 | 0.1 | 0.1 |
| 344 | 1 | 0.1 | 0.1 |
| 358 | 1 | 0.1 | 0.1 |
| 360 | 1 | 0.1 | 0.1 |
| 365 | 1 | 0.1 | 0.1 |
| 370 | 1 | 0.1 | 0.1 |
| 400 | 1 | 0.1 | 0.1 |
| 410 | 1 | 0.1 | 0.1 |
| 50 | 1 | 0.1 | 0.1 |
| 60 | 1 | 0.1 | 0.1 |
| 65 | 1 | 0.1 | 0.1 |
| 7 | 1 | 0.1 | 0.1 |
| 71 | 1 | 0.1 | 0.1 |
| 78 | 1 | 0.1 | 0.1 |
| 80 | 2 | 0.1 | 0.1 |
| 84 | 1 | 0.1 | 0.1 |
| 92 | 1 | 0.1 | 0.1 |
| 97 | 1 | 0.1 | 0.1 |
| 98 | 1 | 0.1 | 0.1 |
| “NA” | 223 | 12.7 | 12.7 |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| 0 | 7 | 0.4 | 0.4 |
| 1 | 2 | 0.1 | 0.1 |
| 1 7 | 1 | 0.1 | 0.1 |
| 110 | 1 | 0.1 | 0.1 |
| 111 | 1 | 0.1 | 0.1 |
| 113 | 1 | 0.1 | 0.1 |
| 175 | 1 | 0.1 | 0.1 |
| 2 | 2 | 0.1 | 0.1 |
| 22 | 1 | 0.1 | 0.1 |
| 3 | 1 | 0.1 | 0.1 |
| 37 | 1 | 0.1 | 0.1 |
| 45 | 1 | 0.1 | 0.1 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 2 | 0.1 | 0.1 |
| 65 | 1 | 0.1 | 0.1 |
| 7 | 1 | 0.1 | 0.1 |
| 76 | 1 | 0.1 | 0.1 |
| 82 | 1 | 0.1 | 0.1 |
| 90 | 1 | 0.1 | 0.1 |
| 91 | 1 | 0.1 | 0.1 |
| “NA” | 1725 | 98.3 | 98.3 |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f2lbs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f2lbs")
| n | % | val% | |
|---|---|---|---|
| 140 | 1 | 6.2 | 6.2 |
| 179 | 1 | 6.2 | 6.2 |
| 185 | 2 | 12.5 | 12.5 |
| 187 | 1 | 6.2 | 6.2 |
| 188 | 1 | 6.2 | 6.2 |
| 189 | 1 | 6.2 | 6.2 |
| 190 | 1 | 6.2 | 6.2 |
| 200 | 1 | 6.2 | 6.2 |
| 207 | 1 | 6.2 | 6.2 |
| 210 | 1 | 6.2 | 6.2 |
| 242 | 1 | 6.2 | 6.2 |
| 243 | 1 | 6.2 | 6.2 |
| 259 | 1 | 6.2 | 6.2 |
| 275 | 1 | 6.2 | 6.2 |
| “NA” | 1 | 6.2 | 6.2 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f2kgs,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "How much do you current weight? (kgs)")
| n | % | val% | |
|---|---|---|---|
| “NA” | 16 | 100 | 100 |
| Total | 16 | 100 | 100 |
rm(temp.dd)
f3 <- as.factor(d[,"f3"])
levels(f3) <- list(Per_week_5_7="4",
Per_week_3_4="3",
Per_week_1_2="2",
Per_week_less_1="1",
Scantron_Error="*")
f3 <- ordered(f3, c("Per_week_5_7","Per_week_3_4","Per_week_1_2","Per_week_less_1","Scantron_Error"))
new.d <- data.frame(new.d, f3)
new.d <- apply_labels(new.d, f3 = "exercise")
temp.d <- data.frame (new.d, f3)
result<-questionr::freq(temp.d$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 580 | 16.3 | 17.6 | 16.3 | 17.6 |
| Per_week_3_4 | 960 | 27.0 | 29.1 | 43.3 | 46.7 |
| Per_week_1_2 | 934 | 26.3 | 28.3 | 69.6 | 75.0 |
| Per_week_less_1 | 823 | 23.1 | 24.9 | 92.7 | 99.9 |
| Scantron_Error | 3 | 0.1 | 0.1 | 92.8 | 100.0 |
| NA | 257 | 7.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 88 | 27.4 | 27.8 | 27.4 | 27.8 |
| Per_week_3_4 | 96 | 29.9 | 30.4 | 57.3 | 58.2 |
| Per_week_1_2 | 80 | 24.9 | 25.3 | 82.2 | 83.5 |
| Per_week_less_1 | 52 | 16.2 | 16.5 | 98.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.4 | 100.0 |
| NA | 5 | 1.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 39 | 18.6 | 19.6 | 18.6 | 19.6 |
| Per_week_3_4 | 75 | 35.7 | 37.7 | 54.3 | 57.3 |
| Per_week_1_2 | 54 | 25.7 | 27.1 | 80.0 | 84.4 |
| Per_week_less_1 | 31 | 14.8 | 15.6 | 94.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.8 | 100.0 |
| NA | 11 | 5.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 60 | 19.0 | 20.8 | 19.0 | 20.8 |
| Per_week_3_4 | 92 | 29.2 | 31.9 | 48.3 | 52.8 |
| Per_week_1_2 | 83 | 26.3 | 28.8 | 74.6 | 81.6 |
| Per_week_less_1 | 53 | 16.8 | 18.4 | 91.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.4 | 100.0 |
| NA | 27 | 8.6 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 47 | 13.2 | 14.4 | 13.2 | 14.4 |
| Per_week_3_4 | 78 | 21.9 | 23.9 | 35.1 | 38.3 |
| Per_week_1_2 | 100 | 28.1 | 30.7 | 63.2 | 69.0 |
| Per_week_less_1 | 101 | 28.4 | 31.0 | 91.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.6 | 100.0 |
| NA | 30 | 8.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 84 | 14.4 | 15.6 | 14.4 | 15.6 |
| Per_week_3_4 | 141 | 24.1 | 26.2 | 38.5 | 41.8 |
| Per_week_1_2 | 154 | 26.3 | 28.6 | 64.8 | 70.4 |
| Per_week_less_1 | 159 | 27.2 | 29.6 | 92.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 92.0 | 100.0 |
| NA | 47 | 8.0 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 260 | 14.8 | 16.0 | 14.8 | 16.0 |
| Per_week_3_4 | 476 | 27.1 | 29.4 | 42.0 | 45.4 |
| Per_week_1_2 | 457 | 26.1 | 28.2 | 68.0 | 73.6 |
| Per_week_less_1 | 425 | 24.2 | 26.2 | 92.2 | 99.8 |
| Scantron_Error | 3 | 0.2 | 0.2 | 92.4 | 100.0 |
| NA | 133 | 7.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f3,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F3. How many days per week do you typically get moderate or strenuous exercise")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_7 | 2 | 12.5 | 16.7 | 12.5 | 16.7 |
| Per_week_3_4 | 2 | 12.5 | 16.7 | 25.0 | 33.3 |
| Per_week_1_2 | 6 | 37.5 | 50.0 | 62.5 | 83.3 |
| Per_week_less_1 | 2 | 12.5 | 16.7 | 75.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 75.0 | 100.0 |
| NA | 4 | 25.0 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
f4 <- as.factor(d[,"f4"])
levels(f4) <- list(Less_than_30_min="2",
Between_30_min_1_hour="3",
More_than_1_hour="4",
Do_not_exercise="1",
Scantron_Error="*")
f4 <- ordered(f4, c("Less_than_30_min","Between_30_min_1_hour","More_than_1_hour","Do_not_exercise","Scantron_Error"))
new.d <- data.frame(new.d, f4)
new.d <- apply_labels(new.d, f4 = "how many minutes exercise")
temp.d <- data.frame (new.d, f4)
result<-questionr::freq(temp.d$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 589 | 16.6 | 17.9 | 16.6 | 17.9 |
| Between_30_min_1_hour | 1363 | 38.3 | 41.4 | 54.9 | 59.3 |
| More_than_1_hour | 734 | 20.6 | 22.3 | 75.5 | 81.6 |
| Do_not_exercise | 603 | 17.0 | 18.3 | 92.5 | 99.9 |
| Scantron_Error | 4 | 0.1 | 0.1 | 92.6 | 100.0 |
| NA | 264 | 7.4 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 37 | 11.5 | 11.8 | 11.5 | 11.8 |
| Between_30_min_1_hour | 158 | 49.2 | 50.3 | 60.7 | 62.1 |
| More_than_1_hour | 83 | 25.9 | 26.4 | 86.6 | 88.5 |
| Do_not_exercise | 35 | 10.9 | 11.1 | 97.5 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 97.8 | 100.0 |
| NA | 7 | 2.2 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 33 | 15.7 | 16.8 | 15.7 | 16.8 |
| Between_30_min_1_hour | 90 | 42.9 | 45.7 | 58.6 | 62.4 |
| More_than_1_hour | 61 | 29.0 | 31.0 | 87.6 | 93.4 |
| Do_not_exercise | 13 | 6.2 | 6.6 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 13 | 6.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 51 | 16.2 | 17.8 | 16.2 | 17.8 |
| Between_30_min_1_hour | 122 | 38.7 | 42.5 | 54.9 | 60.3 |
| More_than_1_hour | 78 | 24.8 | 27.2 | 79.7 | 87.5 |
| Do_not_exercise | 36 | 11.4 | 12.5 | 91.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.1 | 100.0 |
| NA | 28 | 8.9 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 84 | 23.6 | 25.8 | 23.6 | 25.8 |
| Between_30_min_1_hour | 118 | 33.1 | 36.3 | 56.7 | 62.2 |
| More_than_1_hour | 62 | 17.4 | 19.1 | 74.2 | 81.2 |
| Do_not_exercise | 61 | 17.1 | 18.8 | 91.3 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.3 | 100.0 |
| NA | 31 | 8.7 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 97 | 16.6 | 18.1 | 16.6 | 18.1 |
| Between_30_min_1_hour | 197 | 33.7 | 36.7 | 50.3 | 54.7 |
| More_than_1_hour | 111 | 19.0 | 20.7 | 69.2 | 75.4 |
| Do_not_exercise | 131 | 22.4 | 24.4 | 91.6 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 91.8 | 100.0 |
| NA | 48 | 8.2 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 286 | 16.3 | 17.6 | 16.3 | 17.6 |
| Between_30_min_1_hour | 669 | 38.1 | 41.3 | 54.4 | 58.9 |
| More_than_1_hour | 338 | 19.3 | 20.9 | 73.7 | 79.8 |
| Do_not_exercise | 326 | 18.6 | 20.1 | 92.3 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.4 | 100.0 |
| NA | 133 | 7.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f4,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f4")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Less_than_30_min | 1 | 6.2 | 8.3 | 6.2 | 8.3 |
| Between_30_min_1_hour | 9 | 56.2 | 75.0 | 62.5 | 83.3 |
| More_than_1_hour | 1 | 6.2 | 8.3 | 68.8 | 91.7 |
| Do_not_exercise | 1 | 6.2 | 8.3 | 75.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 75.0 | 100.0 |
| NA | 4 | 25.0 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
f5 <- as.factor(d[,"f5"])
levels(f5) <- list(Everyday="6",
Per_week_5_6_times="5",
Per_week_3_4_times="4",
Per_week_1_2_times="3",
Per_week_fewer_once="2",
Not_drink="1",
Scantron_Error="*")
f5 <- ordered(f5, c("Per_week_5_6_times","Per_week_3_4_times","Per_week_1_2_times","Per_week_fewer_once","Not_drink","Scantron_Error"))
new.d <- data.frame(new.d, f5)
new.d <- apply_labels(new.d, f5 = "how often drink")
temp.d <- data.frame (new.d, f5)
result<-questionr::freq(temp.d$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 135 | 3.8 | 4.1 | 3.8 | 4.1 |
| Per_week_3_4_times | 390 | 11.0 | 11.8 | 14.8 | 15.9 |
| Per_week_1_2_times | 518 | 14.6 | 15.7 | 29.3 | 31.6 |
| Per_week_fewer_once | 668 | 18.8 | 20.2 | 48.1 | 51.8 |
| Not_drink | 1588 | 44.6 | 48.0 | 92.7 | 99.8 |
| Scantron_Error | 6 | 0.2 | 0.2 | 92.9 | 100.0 |
| NA | 252 | 7.1 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 16 | 5.0 | 5.2 | 5.0 | 5.2 |
| Per_week_3_4_times | 40 | 12.5 | 12.9 | 17.4 | 18.1 |
| Per_week_1_2_times | 42 | 13.1 | 13.5 | 30.5 | 31.6 |
| Per_week_fewer_once | 65 | 20.2 | 21.0 | 50.8 | 52.6 |
| Not_drink | 147 | 45.8 | 47.4 | 96.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 96.6 | 100.0 |
| NA | 11 | 3.4 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 14 | 6.7 | 7.3 | 6.7 | 7.3 |
| Per_week_3_4_times | 22 | 10.5 | 11.5 | 17.1 | 18.8 |
| Per_week_1_2_times | 37 | 17.6 | 19.4 | 34.8 | 38.2 |
| Per_week_fewer_once | 33 | 15.7 | 17.3 | 50.5 | 55.5 |
| Not_drink | 85 | 40.5 | 44.5 | 91.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 91.0 | 100.0 |
| NA | 19 | 9.0 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 13 | 4.1 | 4.5 | 4.1 | 4.5 |
| Per_week_3_4_times | 44 | 14.0 | 15.2 | 18.1 | 19.7 |
| Per_week_1_2_times | 36 | 11.4 | 12.4 | 29.5 | 32.1 |
| Per_week_fewer_once | 60 | 19.0 | 20.7 | 48.6 | 52.8 |
| Not_drink | 136 | 43.2 | 46.9 | 91.7 | 99.7 |
| Scantron_Error | 1 | 0.3 | 0.3 | 92.1 | 100.0 |
| NA | 25 | 7.9 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 10 | 2.8 | 3.0 | 2.8 | 3.0 |
| Per_week_3_4_times | 42 | 11.8 | 12.6 | 14.6 | 15.6 |
| Per_week_1_2_times | 65 | 18.3 | 19.5 | 32.9 | 35.1 |
| Per_week_fewer_once | 63 | 17.7 | 18.9 | 50.6 | 54.1 |
| Not_drink | 151 | 42.4 | 45.3 | 93.0 | 99.4 |
| Scantron_Error | 2 | 0.6 | 0.6 | 93.5 | 100.0 |
| NA | 23 | 6.5 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 25 | 4.3 | 4.6 | 4.3 | 4.6 |
| Per_week_3_4_times | 65 | 11.1 | 12.0 | 15.4 | 16.6 |
| Per_week_1_2_times | 90 | 15.4 | 16.6 | 30.8 | 33.3 |
| Per_week_fewer_once | 99 | 16.9 | 18.3 | 47.7 | 51.6 |
| Not_drink | 261 | 44.6 | 48.2 | 92.3 | 99.8 |
| Scantron_Error | 1 | 0.2 | 0.2 | 92.5 | 100.0 |
| NA | 44 | 7.5 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 57 | 3.2 | 3.5 | 3.2 | 3.5 |
| Per_week_3_4_times | 174 | 9.9 | 10.7 | 13.2 | 14.2 |
| Per_week_1_2_times | 247 | 14.1 | 15.2 | 27.3 | 29.4 |
| Per_week_fewer_once | 347 | 19.8 | 21.4 | 47.0 | 50.8 |
| Not_drink | 798 | 45.5 | 49.1 | 92.5 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 92.6 | 100.0 |
| NA | 129 | 7.4 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f5,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f5")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Per_week_5_6_times | 0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Per_week_3_4_times | 3 | 18.8 | 20.0 | 18.8 | 20.0 |
| Per_week_1_2_times | 1 | 6.2 | 6.7 | 25.0 | 26.7 |
| Per_week_fewer_once | 1 | 6.2 | 6.7 | 31.2 | 33.3 |
| Not_drink | 10 | 62.5 | 66.7 | 93.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.8 | 100.0 |
| NA | 1 | 6.2 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
f6 <- as.factor(d[,"f6"])
levels(f6) <- list(Three_or_more="3",
One_to_two_drinks="2",
Not_drink="1",
Scantron_Error="*")
f6 <- ordered(f6, c("Three_or_more","One_to_two_drinks","Not_drink","Scantron_Error"))
new.d <- data.frame(new.d, f6)
new.d <- apply_labels(new.d, f6 = "how many drinks")
temp.d <- data.frame (new.d, f6)
result<-questionr::freq(temp.d$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 332 | 9.3 | 10.5 | 9.3 | 10.5 |
| One_to_two_drinks | 1467 | 41.2 | 46.3 | 50.6 | 56.8 |
| Not_drink | 1368 | 38.5 | 43.2 | 89.0 | 100.0 |
| Scantron_Error | 1 | 0.0 | 0.0 | 89.1 | 100.0 |
| NA | 389 | 10.9 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 22 | 6.9 | 7.0 | 6.9 | 7.0 |
| One_to_two_drinks | 141 | 43.9 | 44.9 | 50.8 | 51.9 |
| Not_drink | 151 | 47.0 | 48.1 | 97.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 97.8 | 100.0 |
| NA | 7 | 2.2 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 17 | 8.1 | 9.1 | 8.1 | 9.1 |
| One_to_two_drinks | 103 | 49.0 | 55.4 | 57.1 | 64.5 |
| Not_drink | 66 | 31.4 | 35.5 | 88.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 88.6 | 100.0 |
| NA | 24 | 11.4 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 36 | 11.4 | 12.6 | 11.4 | 12.6 |
| One_to_two_drinks | 132 | 41.9 | 46.3 | 53.3 | 58.9 |
| Not_drink | 117 | 37.1 | 41.1 | 90.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 90.5 | 100.0 |
| NA | 30 | 9.5 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 32 | 9.0 | 10.4 | 9.0 | 10.4 |
| One_to_two_drinks | 151 | 42.4 | 49.2 | 51.4 | 59.6 |
| Not_drink | 124 | 34.8 | 40.4 | 86.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 86.2 | 100.0 |
| NA | 49 | 13.8 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 74 | 12.6 | 13.5 | 12.6 | 13.5 |
| One_to_two_drinks | 225 | 38.5 | 41.1 | 51.1 | 54.7 |
| Not_drink | 248 | 42.4 | 45.3 | 93.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 93.5 | 100.0 |
| NA | 38 | 6.5 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 150 | 8.6 | 9.9 | 8.6 | 9.9 |
| One_to_two_drinks | 711 | 40.5 | 46.9 | 49.1 | 56.8 |
| Not_drink | 654 | 37.3 | 43.1 | 86.4 | 99.9 |
| Scantron_Error | 1 | 0.1 | 0.1 | 86.4 | 100.0 |
| NA | 238 | 13.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f6,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "f6")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Three_or_more | 1 | 6.2 | 7.7 | 6.2 | 7.7 |
| One_to_two_drinks | 4 | 25.0 | 30.8 | 31.2 | 38.5 |
| Not_drink | 8 | 50.0 | 61.5 | 81.2 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 81.2 | 100.0 |
| NA | 3 | 18.8 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
rm(temp.dd)
f7 <- as.factor(d[,"f7"])
levels(f7) <- list(Yes="2",
No="1",
Scantron_Error="*")
f7 <- ordered(f7, c("No","Yes","Scantron_Error"))
new.d <- data.frame(new.d, f7)
new.d <- apply_labels(new.d, f7 = "smoke")
temp.d <- data.frame (new.d, f7)
result<-questionr::freq(temp.d$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 1806 | 50.8 | 53.6 | 50.8 | 53.6 |
| Yes | 1565 | 44.0 | 46.4 | 94.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.8 | 100.0 |
| NA | 186 | 5.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
f7age <- d[,"f7age"]
f7age[which(f7age=="555")]<-"Less_than_10"
f7age[which(f7age=="777")]<-"More_than_75"
new.d <- data.frame(new.d, f7age)
new.d <- apply_labels(new.d, f7age = "age start to smoke")
temp.d <- data.frame (new.d, f7age)
result<-questionr::freq(temp.d$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 0 | 5 | 0.1 | 0.1 |
| 1 | 2 | 0.1 | 0.1 |
| 10 | 12 | 0.3 | 0.3 |
| 11 | 6 | 0.2 | 0.2 |
| 12 | 25 | 0.7 | 0.7 |
| 13 | 40 | 1.1 | 1.1 |
| 14 | 47 | 1.3 | 1.3 |
| 15 | 111 | 3.1 | 3.1 |
| 16 | 130 | 3.7 | 3.7 |
| 17 | 127 | 3.6 | 3.6 |
| 18 | 198 | 5.6 | 5.6 |
| 19 | 107 | 3.0 | 3.0 |
| 20 | 111 | 3.1 | 3.1 |
| 21 | 61 | 1.7 | 1.7 |
| 22 | 47 | 1.3 | 1.3 |
| 23 | 29 | 0.8 | 0.8 |
| 24 | 15 | 0.4 | 0.4 |
| 25 | 42 | 1.2 | 1.2 |
| 26 | 9 | 0.3 | 0.3 |
| 27 | 13 | 0.4 | 0.4 |
| 28 | 14 | 0.4 | 0.4 |
| 29 | 2 | 0.1 | 0.1 |
| 3 | 1 | 0.0 | 0.0 |
| 30 | 30 | 0.8 | 0.8 |
| 31 | 2 | 0.1 | 0.1 |
| 32 | 6 | 0.2 | 0.2 |
| 33 | 3 | 0.1 | 0.1 |
| 34 | 5 | 0.1 | 0.1 |
| 35 | 18 | 0.5 | 0.5 |
| 36 | 1 | 0.0 | 0.0 |
| 38 | 2 | 0.1 | 0.1 |
| 4 | 1 | 0.0 | 0.0 |
| 40 | 7 | 0.2 | 0.2 |
| 41 | 1 | 0.0 | 0.0 |
| 42 | 1 | 0.0 | 0.0 |
| 44 | 1 | 0.0 | 0.0 |
| 45 | 3 | 0.1 | 0.1 |
| 48 | 1 | 0.0 | 0.0 |
| 49 | 3 | 0.1 | 0.1 |
| 5 | 1 | 0.0 | 0.0 |
| 50 | 3 | 0.1 | 0.1 |
| 54 | 2 | 0.1 | 0.1 |
| 55 | 1 | 0.0 | 0.0 |
| 56 | 1 | 0.0 | 0.0 |
| 59 | 1 | 0.0 | 0.0 |
| 60 | 1 | 0.0 | 0.0 |
| 62 | 1 | 0.0 | 0.0 |
| 7 | 2 | 0.1 | 0.1 |
| 8 | 2 | 0.1 | 0.1 |
| 9 | 4 | 0.1 | 0.1 |
| Less_than_10 | 2 | 0.1 | 0.1 |
| “NA” | 2297 | 64.6 | 64.6 |
| Total | 3557 | 100.0 | 100.0 |
f7a <- as.factor(d[,"f7a"])
levels(f7a) <- list(One_to_five="1",
Six_to_ten="2",
Eleven_to_twenty="3",
Twentyone_to_Thirty="4",
Older_31="5",
Scantron_Error="*")
f7a <- ordered(f7a, c("One_to_five","Six_to_ten","Eleven_to_twenty","Twentyone_to_Thirty","Older_31","Scantron_Error"))
new.d <- data.frame(new.d, f7a)
new.d <- apply_labels(new.d, f7a = "How many cigarettes per day")
temp.d <- data.frame (new.d, f7a)
result<-questionr::freq(temp.d$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 569 | 16.0 | 35.7 | 16.0 | 35.7 |
| Six_to_ten | 492 | 13.8 | 30.8 | 29.8 | 66.5 |
| Eleven_to_twenty | 387 | 10.9 | 24.3 | 40.7 | 90.8 |
| Twentyone_to_Thirty | 102 | 2.9 | 6.4 | 43.6 | 97.2 |
| Older_31 | 44 | 1.2 | 2.8 | 44.8 | 99.9 |
| Scantron_Error | 1 | 0.0 | 0.1 | 44.8 | 100.0 |
| NA | 1962 | 55.2 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
f7b <- as.factor(d[,"f7b"])
levels(f7b) <- list(No="1",
Yes="2",
Scantron_Error="*")
new.d <- data.frame(new.d, f7b)
new.d <- apply_labels(new.d, f7b = "quit smoking")
temp.d <- data.frame (new.d, f7b)
result<-questionr::freq(temp.d$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 362 | 10.2 | 22.2 |
| Yes | 1262 | 35.5 | 77.6 |
| Scantron_Error | 3 | 0.1 | 0.2 |
| NA | 1930 | 54.3 | NA |
| Total | 3557 | 100.0 | 100.0 |
f7bage <- d[,"f7bage"]
f7bage[which(f7bage=="555")]<-"Less_than_10"
f7bage[which(f7bage=="777")]<-"More_than_75"
new.d <- data.frame(new.d, f7bage)
new.d <- apply_labels(new.d, f7bage = "age quit smoking")
temp.d <- data.frame (new.d, f7bage)
result<-questionr::freq(temp.d$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 1 | 2 | 0.1 | 0.1 |
| 12 | 1 | 0.0 | 0.0 |
| 15 | 2 | 0.1 | 0.1 |
| 16 | 4 | 0.1 | 0.1 |
| 17 | 6 | 0.2 | 0.2 |
| 18 | 4 | 0.1 | 0.1 |
| 19 | 9 | 0.3 | 0.3 |
| 20 | 24 | 0.7 | 0.7 |
| 21 | 13 | 0.4 | 0.4 |
| 22 | 17 | 0.5 | 0.5 |
| 23 | 25 | 0.7 | 0.7 |
| 24 | 13 | 0.4 | 0.4 |
| 25 | 36 | 1.0 | 1.0 |
| 26 | 15 | 0.4 | 0.4 |
| 27 | 22 | 0.6 | 0.6 |
| 28 | 30 | 0.8 | 0.8 |
| 29 | 17 | 0.5 | 0.5 |
| 30 | 70 | 2.0 | 2.0 |
| 31 | 18 | 0.5 | 0.5 |
| 32 | 17 | 0.5 | 0.5 |
| 33 | 15 | 0.4 | 0.4 |
| 34 | 16 | 0.4 | 0.4 |
| 35 | 63 | 1.8 | 1.8 |
| 36 | 15 | 0.4 | 0.4 |
| 37 | 11 | 0.3 | 0.3 |
| 38 | 24 | 0.7 | 0.7 |
| 39 | 12 | 0.3 | 0.3 |
| 4 | 2 | 0.1 | 0.1 |
| 40 | 77 | 2.2 | 2.2 |
| 41 | 13 | 0.4 | 0.4 |
| 42 | 21 | 0.6 | 0.6 |
| 43 | 18 | 0.5 | 0.5 |
| 44 | 11 | 0.3 | 0.3 |
| 45 | 53 | 1.5 | 1.5 |
| 46 | 12 | 0.3 | 0.3 |
| 47 | 14 | 0.4 | 0.4 |
| 48 | 20 | 0.6 | 0.6 |
| 49 | 21 | 0.6 | 0.6 |
| 50 | 79 | 2.2 | 2.2 |
| 51 | 17 | 0.5 | 0.5 |
| 52 | 21 | 0.6 | 0.6 |
| 53 | 13 | 0.4 | 0.4 |
| 54 | 14 | 0.4 | 0.4 |
| 55 | 34 | 1.0 | 1.0 |
| 56 | 19 | 0.5 | 0.5 |
| 57 | 14 | 0.4 | 0.4 |
| 58 | 24 | 0.7 | 0.7 |
| 59 | 16 | 0.4 | 0.4 |
| 6 | 1 | 0.0 | 0.0 |
| 60 | 32 | 0.9 | 0.9 |
| 61 | 11 | 0.3 | 0.3 |
| 62 | 17 | 0.5 | 0.5 |
| 63 | 18 | 0.5 | 0.5 |
| 64 | 12 | 0.3 | 0.3 |
| 65 | 30 | 0.8 | 0.8 |
| 66 | 15 | 0.4 | 0.4 |
| 67 | 14 | 0.4 | 0.4 |
| 68 | 11 | 0.3 | 0.3 |
| 69 | 11 | 0.3 | 0.3 |
| 7 | 1 | 0.0 | 0.0 |
| 70 | 12 | 0.3 | 0.3 |
| 71 | 3 | 0.1 | 0.1 |
| 72 | 1 | 0.0 | 0.0 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.0 | 0.0 |
| 75 | 1 | 0.0 | 0.0 |
| 76 | 2 | 0.1 | 0.1 |
| 78 | 1 | 0.0 | 0.0 |
| 8 | 2 | 0.1 | 0.1 |
| 9 | 1 | 0.0 | 0.0 |
| “NA” | 2344 | 65.9 | 65.9 |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 166 | 51.7 | 52.5 | 51.7 | 52.5 |
| Yes | 150 | 46.7 | 47.5 | 98.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 98.4 | 100.0 |
| NA | 5 | 1.6 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 10 | 2 | 0.6 | 0.6 |
| 12 | 2 | 0.6 | 0.6 |
| 13 | 6 | 1.9 | 1.9 |
| 14 | 3 | 0.9 | 0.9 |
| 15 | 10 | 3.1 | 3.1 |
| 16 | 13 | 4.0 | 4.0 |
| 17 | 13 | 4.0 | 4.0 |
| 18 | 14 | 4.4 | 4.4 |
| 19 | 11 | 3.4 | 3.4 |
| 20 | 11 | 3.4 | 3.4 |
| 21 | 11 | 3.4 | 3.4 |
| 22 | 9 | 2.8 | 2.8 |
| 23 | 3 | 0.9 | 0.9 |
| 25 | 3 | 0.9 | 0.9 |
| 26 | 2 | 0.6 | 0.6 |
| 27 | 1 | 0.3 | 0.3 |
| 28 | 2 | 0.6 | 0.6 |
| 30 | 1 | 0.3 | 0.3 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 1 | 0.3 | 0.3 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 3 | 0.9 | 0.9 |
| 40 | 1 | 0.3 | 0.3 |
| 45 | 1 | 0.3 | 0.3 |
| 48 | 1 | 0.3 | 0.3 |
| “NA” | 195 | 60.7 | 60.7 |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 54 | 16.8 | 36.5 | 16.8 | 36.5 |
| Six_to_ten | 47 | 14.6 | 31.8 | 31.5 | 68.2 |
| Eleven_to_twenty | 37 | 11.5 | 25.0 | 43.0 | 93.2 |
| Twentyone_to_Thirty | 8 | 2.5 | 5.4 | 45.5 | 98.6 |
| Older_31 | 2 | 0.6 | 1.4 | 46.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 46.1 | 100.0 |
| NA | 173 | 53.9 | NA | 100.0 | NA |
| Total | 321 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 20 | 6.2 | 13.6 |
| Yes | 127 | 39.6 | 86.4 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 174 | 54.2 | NA |
| Total | 321 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 19 | 1 | 0.3 | 0.3 |
| 20 | 3 | 0.9 | 0.9 |
| 21 | 1 | 0.3 | 0.3 |
| 23 | 1 | 0.3 | 0.3 |
| 25 | 5 | 1.6 | 1.6 |
| 26 | 4 | 1.2 | 1.2 |
| 27 | 3 | 0.9 | 0.9 |
| 28 | 3 | 0.9 | 0.9 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 6 | 1.9 | 1.9 |
| 31 | 2 | 0.6 | 0.6 |
| 32 | 2 | 0.6 | 0.6 |
| 33 | 1 | 0.3 | 0.3 |
| 34 | 4 | 1.2 | 1.2 |
| 35 | 5 | 1.6 | 1.6 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 1 | 0.3 | 0.3 |
| 38 | 2 | 0.6 | 0.6 |
| 39 | 2 | 0.6 | 0.6 |
| 40 | 8 | 2.5 | 2.5 |
| 42 | 4 | 1.2 | 1.2 |
| 43 | 3 | 0.9 | 0.9 |
| 44 | 2 | 0.6 | 0.6 |
| 45 | 8 | 2.5 | 2.5 |
| 47 | 1 | 0.3 | 0.3 |
| 48 | 2 | 0.6 | 0.6 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 8 | 2.5 | 2.5 |
| 51 | 2 | 0.6 | 0.6 |
| 52 | 8 | 2.5 | 2.5 |
| 53 | 2 | 0.6 | 0.6 |
| 54 | 2 | 0.6 | 0.6 |
| 55 | 2 | 0.6 | 0.6 |
| 56 | 2 | 0.6 | 0.6 |
| 57 | 4 | 1.2 | 1.2 |
| 58 | 4 | 1.2 | 1.2 |
| 59 | 2 | 0.6 | 0.6 |
| 6 | 1 | 0.3 | 0.3 |
| 60 | 3 | 0.9 | 0.9 |
| 62 | 2 | 0.6 | 0.6 |
| 63 | 2 | 0.6 | 0.6 |
| 64 | 3 | 0.9 | 0.9 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 2 | 0.6 | 0.6 |
| 67 | 1 | 0.3 | 0.3 |
| 70 | 2 | 0.6 | 0.6 |
| “NA” | 190 | 59.2 | 59.2 |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 102 | 48.6 | 51.3 | 48.6 | 51.3 |
| Yes | 97 | 46.2 | 48.7 | 94.8 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.8 | 100.0 |
| NA | 11 | 5.2 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7ageE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| X0L | X0L.1 | X0L.2 | val% |
|---|---|---|---|
| 0 | 0 | 0 | NA |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 39 | 18.6 | 39 | 18.6 | 39 |
| Six_to_ten | 28 | 13.3 | 28 | 31.9 | 67 |
| Eleven_to_twenty | 23 | 11.0 | 23 | 42.9 | 90 |
| Twentyone_to_Thirty | 9 | 4.3 | 9 | 47.1 | 99 |
| Older_31 | 1 | 0.5 | 1 | 47.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 47.6 | 100 |
| NA | 110 | 52.4 | NA | 100.0 | NA |
| Total | 210 | 100.0 | 100 | 100.0 | 100 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 12 | 5.7 | 12.5 |
| Yes | 84 | 40.0 | 87.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 114 | 54.3 | NA |
| Total | 210 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 16 | 1 | 0.5 | 0.5 |
| 20 | 3 | 1.4 | 1.4 |
| 21 | 2 | 1.0 | 1.0 |
| 24 | 3 | 1.4 | 1.4 |
| 25 | 3 | 1.4 | 1.4 |
| 26 | 1 | 0.5 | 0.5 |
| 27 | 3 | 1.4 | 1.4 |
| 28 | 4 | 1.9 | 1.9 |
| 30 | 5 | 2.4 | 2.4 |
| 31 | 3 | 1.4 | 1.4 |
| 32 | 2 | 1.0 | 1.0 |
| 33 | 1 | 0.5 | 0.5 |
| 35 | 4 | 1.9 | 1.9 |
| 36 | 3 | 1.4 | 1.4 |
| 37 | 2 | 1.0 | 1.0 |
| 38 | 4 | 1.9 | 1.9 |
| 39 | 2 | 1.0 | 1.0 |
| 40 | 5 | 2.4 | 2.4 |
| 42 | 2 | 1.0 | 1.0 |
| 43 | 2 | 1.0 | 1.0 |
| 45 | 5 | 2.4 | 2.4 |
| 46 | 1 | 0.5 | 0.5 |
| 47 | 1 | 0.5 | 0.5 |
| 49 | 2 | 1.0 | 1.0 |
| 50 | 3 | 1.4 | 1.4 |
| 51 | 1 | 0.5 | 0.5 |
| 52 | 3 | 1.4 | 1.4 |
| 56 | 1 | 0.5 | 0.5 |
| 58 | 1 | 0.5 | 0.5 |
| 59 | 2 | 1.0 | 1.0 |
| 60 | 1 | 0.5 | 0.5 |
| 63 | 2 | 1.0 | 1.0 |
| 65 | 2 | 1.0 | 1.0 |
| 66 | 3 | 1.4 | 1.4 |
| 70 | 1 | 0.5 | 0.5 |
| “NA” | 126 | 60.0 | 60.0 |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 173 | 54.9 | 57.5 | 54.9 | 57.5 |
| Yes | 128 | 40.6 | 42.5 | 95.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 95.6 | 100.0 |
| NA | 14 | 4.4 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 11 | 1 | 0.3 | 0.3 |
| 12 | 1 | 0.3 | 0.3 |
| 13 | 1 | 0.3 | 0.3 |
| 14 | 4 | 1.3 | 1.3 |
| 15 | 8 | 2.5 | 2.5 |
| 16 | 9 | 2.9 | 2.9 |
| 17 | 8 | 2.5 | 2.5 |
| 18 | 15 | 4.8 | 4.8 |
| 19 | 12 | 3.8 | 3.8 |
| 20 | 9 | 2.9 | 2.9 |
| 21 | 6 | 1.9 | 1.9 |
| 22 | 6 | 1.9 | 1.9 |
| 23 | 3 | 1.0 | 1.0 |
| 25 | 6 | 1.9 | 1.9 |
| 27 | 1 | 0.3 | 0.3 |
| 28 | 3 | 1.0 | 1.0 |
| 30 | 2 | 0.6 | 0.6 |
| 32 | 1 | 0.3 | 0.3 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 2 | 0.6 | 0.6 |
| 40 | 1 | 0.3 | 0.3 |
| “NA” | 215 | 68.3 | 68.3 |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 47 | 14.9 | 37.3 | 14.9 | 37.3 |
| Six_to_ten | 42 | 13.3 | 33.3 | 28.3 | 70.6 |
| Eleven_to_twenty | 25 | 7.9 | 19.8 | 36.2 | 90.5 |
| Twentyone_to_Thirty | 9 | 2.9 | 7.1 | 39.0 | 97.6 |
| Older_31 | 3 | 1.0 | 2.4 | 40.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 40.0 | 100.0 |
| NA | 189 | 60.0 | NA | 100.0 | NA |
| Total | 315 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 27 | 8.6 | 20.3 |
| Yes | 106 | 33.7 | 79.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 182 | 57.8 | NA |
| Total | 315 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 12 | 1 | 0.3 | 0.3 |
| 16 | 2 | 0.6 | 0.6 |
| 17 | 1 | 0.3 | 0.3 |
| 20 | 2 | 0.6 | 0.6 |
| 21 | 2 | 0.6 | 0.6 |
| 22 | 1 | 0.3 | 0.3 |
| 23 | 3 | 1.0 | 1.0 |
| 24 | 2 | 0.6 | 0.6 |
| 25 | 3 | 1.0 | 1.0 |
| 27 | 2 | 0.6 | 0.6 |
| 28 | 3 | 1.0 | 1.0 |
| 29 | 1 | 0.3 | 0.3 |
| 30 | 5 | 1.6 | 1.6 |
| 31 | 2 | 0.6 | 0.6 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 2 | 0.6 | 0.6 |
| 34 | 4 | 1.3 | 1.3 |
| 35 | 4 | 1.3 | 1.3 |
| 38 | 1 | 0.3 | 0.3 |
| 39 | 1 | 0.3 | 0.3 |
| 40 | 4 | 1.3 | 1.3 |
| 41 | 1 | 0.3 | 0.3 |
| 42 | 3 | 1.0 | 1.0 |
| 44 | 2 | 0.6 | 0.6 |
| 45 | 4 | 1.3 | 1.3 |
| 46 | 1 | 0.3 | 0.3 |
| 47 | 3 | 1.0 | 1.0 |
| 48 | 3 | 1.0 | 1.0 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 8 | 2.5 | 2.5 |
| 51 | 1 | 0.3 | 0.3 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 3 | 1.0 | 1.0 |
| 54 | 3 | 1.0 | 1.0 |
| 55 | 3 | 1.0 | 1.0 |
| 56 | 1 | 0.3 | 0.3 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 2 | 0.6 | 0.6 |
| 64 | 4 | 1.3 | 1.3 |
| 65 | 3 | 1.0 | 1.0 |
| 67 | 1 | 0.3 | 0.3 |
| 72 | 1 | 0.3 | 0.3 |
| “NA” | 212 | 67.3 | 67.3 |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 175 | 49.2 | 52.2 | 49.2 | 52.2 |
| Yes | 160 | 44.9 | 47.8 | 94.1 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.1 | 100.0 |
| NA | 21 | 5.9 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.3 | 0.3 |
| 10 | 1 | 0.3 | 0.3 |
| 12 | 5 | 1.4 | 1.4 |
| 13 | 3 | 0.8 | 0.8 |
| 14 | 8 | 2.2 | 2.2 |
| 15 | 12 | 3.4 | 3.4 |
| 16 | 15 | 4.2 | 4.2 |
| 17 | 11 | 3.1 | 3.1 |
| 18 | 19 | 5.3 | 5.3 |
| 19 | 10 | 2.8 | 2.8 |
| 20 | 9 | 2.5 | 2.5 |
| 21 | 3 | 0.8 | 0.8 |
| 22 | 2 | 0.6 | 0.6 |
| 23 | 3 | 0.8 | 0.8 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 6 | 1.7 | 1.7 |
| 26 | 1 | 0.3 | 0.3 |
| 27 | 1 | 0.3 | 0.3 |
| 30 | 2 | 0.6 | 0.6 |
| 31 | 1 | 0.3 | 0.3 |
| 32 | 1 | 0.3 | 0.3 |
| 33 | 1 | 0.3 | 0.3 |
| 35 | 1 | 0.3 | 0.3 |
| 4 | 1 | 0.3 | 0.3 |
| 54 | 1 | 0.3 | 0.3 |
| 7 | 1 | 0.3 | 0.3 |
| 8 | 1 | 0.3 | 0.3 |
| 9 | 1 | 0.3 | 0.3 |
| “NA” | 234 | 65.7 | 65.7 |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 53 | 14.9 | 31.9 | 14.9 | 31.9 |
| Six_to_ten | 45 | 12.6 | 27.1 | 27.5 | 59.0 |
| Eleven_to_twenty | 51 | 14.3 | 30.7 | 41.9 | 89.8 |
| Twentyone_to_Thirty | 14 | 3.9 | 8.4 | 45.8 | 98.2 |
| Older_31 | 3 | 0.8 | 1.8 | 46.6 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 46.6 | 100.0 |
| NA | 190 | 53.4 | NA | 100.0 | NA |
| Total | 356 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 50 | 14.0 | 30.5 |
| Yes | 113 | 31.7 | 68.9 |
| Scantron_Error | 1 | 0.3 | 0.6 |
| NA | 192 | 53.9 | NA |
| Total | 356 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.3 | 0.3 |
| 17 | 1 | 0.3 | 0.3 |
| 18 | 1 | 0.3 | 0.3 |
| 22 | 1 | 0.3 | 0.3 |
| 23 | 2 | 0.6 | 0.6 |
| 24 | 1 | 0.3 | 0.3 |
| 25 | 4 | 1.1 | 1.1 |
| 26 | 2 | 0.6 | 0.6 |
| 27 | 2 | 0.6 | 0.6 |
| 28 | 3 | 0.8 | 0.8 |
| 30 | 10 | 2.8 | 2.8 |
| 32 | 4 | 1.1 | 1.1 |
| 34 | 1 | 0.3 | 0.3 |
| 35 | 5 | 1.4 | 1.4 |
| 36 | 1 | 0.3 | 0.3 |
| 37 | 1 | 0.3 | 0.3 |
| 38 | 3 | 0.8 | 0.8 |
| 39 | 1 | 0.3 | 0.3 |
| 40 | 4 | 1.1 | 1.1 |
| 41 | 3 | 0.8 | 0.8 |
| 43 | 3 | 0.8 | 0.8 |
| 44 | 1 | 0.3 | 0.3 |
| 45 | 5 | 1.4 | 1.4 |
| 46 | 2 | 0.6 | 0.6 |
| 49 | 1 | 0.3 | 0.3 |
| 50 | 8 | 2.2 | 2.2 |
| 52 | 1 | 0.3 | 0.3 |
| 53 | 2 | 0.6 | 0.6 |
| 55 | 8 | 2.2 | 2.2 |
| 56 | 4 | 1.1 | 1.1 |
| 57 | 2 | 0.6 | 0.6 |
| 58 | 2 | 0.6 | 0.6 |
| 59 | 1 | 0.3 | 0.3 |
| 60 | 2 | 0.6 | 0.6 |
| 61 | 2 | 0.6 | 0.6 |
| 62 | 3 | 0.8 | 0.8 |
| 63 | 2 | 0.6 | 0.6 |
| 65 | 2 | 0.6 | 0.6 |
| 66 | 1 | 0.3 | 0.3 |
| 68 | 2 | 0.6 | 0.6 |
| 69 | 2 | 0.6 | 0.6 |
| 71 | 1 | 0.3 | 0.3 |
| 78 | 1 | 0.3 | 0.3 |
| 9 | 1 | 0.3 | 0.3 |
| “NA” | 246 | 69.1 | 69.1 |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 260 | 44.4 | 47.3 | 44.4 | 47.3 |
| Yes | 290 | 49.6 | 52.7 | 94.0 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.0 | 100.0 |
| NA | 35 | 6.0 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 0 | 1 | 0.2 | 0.2 |
| 10 | 3 | 0.5 | 0.5 |
| 12 | 4 | 0.7 | 0.7 |
| 13 | 6 | 1.0 | 1.0 |
| 14 | 9 | 1.5 | 1.5 |
| 15 | 22 | 3.8 | 3.8 |
| 16 | 25 | 4.3 | 4.3 |
| 17 | 30 | 5.1 | 5.1 |
| 18 | 38 | 6.5 | 6.5 |
| 19 | 16 | 2.7 | 2.7 |
| 20 | 16 | 2.7 | 2.7 |
| 21 | 11 | 1.9 | 1.9 |
| 22 | 8 | 1.4 | 1.4 |
| 23 | 1 | 0.2 | 0.2 |
| 24 | 2 | 0.3 | 0.3 |
| 25 | 6 | 1.0 | 1.0 |
| 26 | 1 | 0.2 | 0.2 |
| 27 | 1 | 0.2 | 0.2 |
| 28 | 7 | 1.2 | 1.2 |
| 3 | 1 | 0.2 | 0.2 |
| 30 | 6 | 1.0 | 1.0 |
| 31 | 1 | 0.2 | 0.2 |
| 32 | 2 | 0.3 | 0.3 |
| 34 | 1 | 0.2 | 0.2 |
| 35 | 3 | 0.5 | 0.5 |
| 40 | 1 | 0.2 | 0.2 |
| 56 | 1 | 0.2 | 0.2 |
| 62 | 1 | 0.2 | 0.2 |
| 9 | 2 | 0.3 | 0.3 |
| “NA” | 359 | 61.4 | 61.4 |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 86 | 14.7 | 29.1 | 14.7 | 29.1 |
| Six_to_ten | 97 | 16.6 | 32.8 | 31.3 | 61.8 |
| Eleven_to_twenty | 84 | 14.4 | 28.4 | 45.6 | 90.2 |
| Twentyone_to_Thirty | 16 | 2.7 | 5.4 | 48.4 | 95.6 |
| Older_31 | 12 | 2.1 | 4.1 | 50.4 | 99.7 |
| Scantron_Error | 1 | 0.2 | 0.3 | 50.6 | 100.0 |
| NA | 289 | 49.4 | NA | 100.0 | NA |
| Total | 585 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 84 | 14.4 | 28.3 |
| Yes | 211 | 36.1 | 71.0 |
| Scantron_Error | 2 | 0.3 | 0.7 |
| NA | 288 | 49.2 | NA |
| Total | 585 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 17 | 1 | 0.2 | 0.2 |
| 19 | 2 | 0.3 | 0.3 |
| 20 | 5 | 0.9 | 0.9 |
| 21 | 2 | 0.3 | 0.3 |
| 22 | 3 | 0.5 | 0.5 |
| 23 | 1 | 0.2 | 0.2 |
| 25 | 6 | 1.0 | 1.0 |
| 26 | 1 | 0.2 | 0.2 |
| 27 | 3 | 0.5 | 0.5 |
| 28 | 2 | 0.3 | 0.3 |
| 29 | 1 | 0.2 | 0.2 |
| 30 | 20 | 3.4 | 3.4 |
| 31 | 1 | 0.2 | 0.2 |
| 32 | 1 | 0.2 | 0.2 |
| 33 | 1 | 0.2 | 0.2 |
| 34 | 1 | 0.2 | 0.2 |
| 35 | 10 | 1.7 | 1.7 |
| 36 | 2 | 0.3 | 0.3 |
| 38 | 4 | 0.7 | 0.7 |
| 39 | 2 | 0.3 | 0.3 |
| 4 | 1 | 0.2 | 0.2 |
| 40 | 17 | 2.9 | 2.9 |
| 41 | 2 | 0.3 | 0.3 |
| 42 | 2 | 0.3 | 0.3 |
| 43 | 2 | 0.3 | 0.3 |
| 44 | 4 | 0.7 | 0.7 |
| 45 | 9 | 1.5 | 1.5 |
| 46 | 1 | 0.2 | 0.2 |
| 47 | 4 | 0.7 | 0.7 |
| 48 | 3 | 0.5 | 0.5 |
| 49 | 3 | 0.5 | 0.5 |
| 50 | 12 | 2.1 | 2.1 |
| 51 | 2 | 0.3 | 0.3 |
| 54 | 3 | 0.5 | 0.5 |
| 55 | 12 | 2.1 | 2.1 |
| 56 | 2 | 0.3 | 0.3 |
| 57 | 1 | 0.2 | 0.2 |
| 58 | 7 | 1.2 | 1.2 |
| 60 | 4 | 0.7 | 0.7 |
| 61 | 2 | 0.3 | 0.3 |
| 62 | 4 | 0.7 | 0.7 |
| 63 | 4 | 0.7 | 0.7 |
| 64 | 2 | 0.3 | 0.3 |
| 65 | 6 | 1.0 | 1.0 |
| 66 | 1 | 0.2 | 0.2 |
| 67 | 1 | 0.2 | 0.2 |
| 68 | 2 | 0.3 | 0.3 |
| 69 | 6 | 1.0 | 1.0 |
| 7 | 1 | 0.2 | 0.2 |
| 70 | 3 | 0.5 | 0.5 |
| 71 | 1 | 0.2 | 0.2 |
| 75 | 1 | 0.2 | 0.2 |
| 8 | 1 | 0.2 | 0.2 |
| “NA” | 390 | 66.7 | 66.7 |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 920 | 52.5 | 55.6 | 52.5 | 55.6 |
| Yes | 736 | 42.0 | 44.4 | 94.4 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 94.4 | 100.0 |
| NA | 98 | 5.6 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 0 | 3 | 0.2 | 0.2 |
| 1 | 1 | 0.1 | 0.1 |
| 10 | 6 | 0.3 | 0.3 |
| 11 | 5 | 0.3 | 0.3 |
| 12 | 11 | 0.6 | 0.6 |
| 13 | 20 | 1.1 | 1.1 |
| 14 | 21 | 1.2 | 1.2 |
| 15 | 58 | 3.3 | 3.3 |
| 16 | 56 | 3.2 | 3.2 |
| 17 | 64 | 3.6 | 3.6 |
| 18 | 104 | 5.9 | 5.9 |
| 19 | 46 | 2.6 | 2.6 |
| 20 | 58 | 3.3 | 3.3 |
| 21 | 25 | 1.4 | 1.4 |
| 22 | 17 | 1.0 | 1.0 |
| 23 | 15 | 0.9 | 0.9 |
| 24 | 8 | 0.5 | 0.5 |
| 25 | 19 | 1.1 | 1.1 |
| 26 | 3 | 0.2 | 0.2 |
| 27 | 9 | 0.5 | 0.5 |
| 28 | 2 | 0.1 | 0.1 |
| 29 | 2 | 0.1 | 0.1 |
| 30 | 18 | 1.0 | 1.0 |
| 32 | 1 | 0.1 | 0.1 |
| 33 | 1 | 0.1 | 0.1 |
| 35 | 8 | 0.5 | 0.5 |
| 38 | 2 | 0.1 | 0.1 |
| 40 | 3 | 0.2 | 0.2 |
| 41 | 1 | 0.1 | 0.1 |
| 42 | 1 | 0.1 | 0.1 |
| 44 | 1 | 0.1 | 0.1 |
| 45 | 1 | 0.1 | 0.1 |
| 49 | 3 | 0.2 | 0.2 |
| 5 | 1 | 0.1 | 0.1 |
| 50 | 3 | 0.2 | 0.2 |
| 54 | 1 | 0.1 | 0.1 |
| 55 | 1 | 0.1 | 0.1 |
| 60 | 1 | 0.1 | 0.1 |
| 7 | 1 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| 9 | 1 | 0.1 | 0.1 |
| Less_than_10 | 2 | 0.1 | 0.1 |
| “NA” | 1149 | 65.5 | 65.5 |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 284 | 16.2 | 37.7 | 16.2 | 37.7 |
| Six_to_ten | 233 | 13.3 | 30.9 | 29.5 | 68.7 |
| Eleven_to_twenty | 167 | 9.5 | 22.2 | 39.0 | 90.8 |
| Twentyone_to_Thirty | 46 | 2.6 | 6.1 | 41.6 | 96.9 |
| Older_31 | 23 | 1.3 | 3.1 | 42.9 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 42.9 | 100.0 |
| NA | 1001 | 57.1 | NA | 100.0 | NA |
| Total | 1754 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 168 | 9.6 | 21.4 |
| Yes | 616 | 35.1 | 78.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 970 | 55.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 1 | 1 | 0.1 | 0.1 |
| 15 | 2 | 0.1 | 0.1 |
| 16 | 1 | 0.1 | 0.1 |
| 17 | 3 | 0.2 | 0.2 |
| 18 | 3 | 0.2 | 0.2 |
| 19 | 6 | 0.3 | 0.3 |
| 20 | 11 | 0.6 | 0.6 |
| 21 | 6 | 0.3 | 0.3 |
| 22 | 12 | 0.7 | 0.7 |
| 23 | 18 | 1.0 | 1.0 |
| 24 | 6 | 0.3 | 0.3 |
| 25 | 15 | 0.9 | 0.9 |
| 26 | 7 | 0.4 | 0.4 |
| 27 | 9 | 0.5 | 0.5 |
| 28 | 15 | 0.9 | 0.9 |
| 29 | 14 | 0.8 | 0.8 |
| 30 | 24 | 1.4 | 1.4 |
| 31 | 10 | 0.6 | 0.6 |
| 32 | 7 | 0.4 | 0.4 |
| 33 | 10 | 0.6 | 0.6 |
| 34 | 6 | 0.3 | 0.3 |
| 35 | 35 | 2.0 | 2.0 |
| 36 | 8 | 0.5 | 0.5 |
| 37 | 7 | 0.4 | 0.4 |
| 38 | 10 | 0.6 | 0.6 |
| 39 | 4 | 0.2 | 0.2 |
| 4 | 1 | 0.1 | 0.1 |
| 40 | 38 | 2.2 | 2.2 |
| 41 | 7 | 0.4 | 0.4 |
| 42 | 9 | 0.5 | 0.5 |
| 43 | 8 | 0.5 | 0.5 |
| 44 | 2 | 0.1 | 0.1 |
| 45 | 22 | 1.3 | 1.3 |
| 46 | 7 | 0.4 | 0.4 |
| 47 | 5 | 0.3 | 0.3 |
| 48 | 12 | 0.7 | 0.7 |
| 49 | 13 | 0.7 | 0.7 |
| 50 | 40 | 2.3 | 2.3 |
| 51 | 11 | 0.6 | 0.6 |
| 52 | 8 | 0.5 | 0.5 |
| 53 | 6 | 0.3 | 0.3 |
| 54 | 6 | 0.3 | 0.3 |
| 55 | 9 | 0.5 | 0.5 |
| 56 | 9 | 0.5 | 0.5 |
| 57 | 5 | 0.3 | 0.3 |
| 58 | 8 | 0.5 | 0.5 |
| 59 | 10 | 0.6 | 0.6 |
| 60 | 19 | 1.1 | 1.1 |
| 61 | 5 | 0.3 | 0.3 |
| 62 | 8 | 0.5 | 0.5 |
| 63 | 8 | 0.5 | 0.5 |
| 64 | 3 | 0.2 | 0.2 |
| 65 | 15 | 0.9 | 0.9 |
| 66 | 8 | 0.5 | 0.5 |
| 67 | 11 | 0.6 | 0.6 |
| 68 | 7 | 0.4 | 0.4 |
| 69 | 3 | 0.2 | 0.2 |
| 70 | 6 | 0.3 | 0.3 |
| 71 | 1 | 0.1 | 0.1 |
| 73 | 2 | 0.1 | 0.1 |
| 74 | 1 | 0.1 | 0.1 |
| 76 | 2 | 0.1 | 0.1 |
| 8 | 1 | 0.1 | 0.1 |
| “NA” | 1168 | 66.6 | 66.6 |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$f7,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7. Have you ever smoked at least 100 cigarettes in your lifetime?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| No | 10 | 62.5 | 71.4 | 62.5 | 71.4 |
| Yes | 4 | 25.0 | 28.6 | 87.5 | 100.0 |
| Scantron_Error | 0 | 0.0 | 0.0 | 87.5 | 100.0 |
| NA | 2 | 12.5 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100.0 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7age,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "If yes, At what age did you start smoking on a regular basis (at least one cigarette/day)?")
| n | % | val% | |
|---|---|---|---|
| 16 | 1 | 6.2 | 6.2 |
| 19 | 1 | 6.2 | 6.2 |
| 21 | 1 | 6.2 | 6.2 |
| 23 | 1 | 6.2 | 6.2 |
| “NA” | 12 | 75.0 | 75.0 |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7a,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7a. How many cigarettes do you (or did you) usually smoke per day?")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| One_to_five | 6 | 37.5 | 100 | 37.5 | 100 |
| Six_to_ten | 0 | 0.0 | 0 | 37.5 | 100 |
| Eleven_to_twenty | 0 | 0.0 | 0 | 37.5 | 100 |
| Twentyone_to_Thirty | 0 | 0.0 | 0 | 37.5 | 100 |
| Older_31 | 0 | 0.0 | 0 | 37.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 | 37.5 | 100 |
| NA | 10 | 62.5 | NA | 100.0 | NA |
| Total | 16 | 100.0 | 100 | 100.0 | 100 |
result<-questionr::freq(temp.dd$f7b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7b. Have you quit smoking?")
| n | % | val% | |
|---|---|---|---|
| No | 1 | 6.2 | 16.7 |
| Yes | 5 | 31.2 | 83.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 10 | 62.5 | NA |
| Total | 16 | 100.0 | 100.0 |
result<-questionr::freq(temp.dd$f7bage,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "F7BAge. If yes, At what age did you quit?")
| n | % | val% | |
|---|---|---|---|
| 24 | 1 | 6.2 | 6.2 |
| 40 | 1 | 6.2 | 6.2 |
| 42 | 1 | 6.2 | 6.2 |
| 60 | 1 | 6.2 | 6.2 |
| “NA” | 12 | 75.0 | 75.0 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
g1 <- as.factor(d[,"g1"])
levels(g1) <- list(Married_partner="1",
Separated="2",
Divorced="3",
Widowed="4",
Never_Married="5",
Scantron_Error="*")
g1 <- ordered(g1, c("Married_partner","Separated","Divorced","Widowed","Never_Married","Scantron_Error"))
new.d <- data.frame(new.d, g1)
new.d <- apply_labels(new.d, g1 = "marital status")
temp.d <- data.frame (new.d, g1)
result<-questionr::freq(temp.d$g1,cum=TRUE,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | %cum | val%cum | |
|---|---|---|---|---|---|
| Married_partner | 2239 | 62.9 | 64.4 | 62.9 | 64.4 |
| Separated | 123 | 3.5 | 3.5 | 66.4 | 68.0 |
| Divorced | 571 | 16.1 | 16.4 | 82.5 | 84.4 |
| Widowed | 209 | 5.9 | 6.0 | 88.3 | 90.4 |
| Never_Married | 332 | 9.3 | 9.6 | 97.7 | 99.9 |
| Scantron_Error | 2 | 0.1 | 0.1 | 97.7 | 100.0 |
| NA | 81 | 2.3 | NA | 100.0 | NA |
| Total | 3557 | 100.0 | 100.0 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 187 | 58.3 | 58.8 |
| Separated | 9 | 2.8 | 2.8 |
| Divorced | 66 | 20.6 | 20.8 |
| Widowed | 13 | 4.0 | 4.1 |
| Never_Married | 43 | 13.4 | 13.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 0.9 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 132 | 62.9 | 63.8 |
| Separated | 5 | 2.4 | 2.4 |
| Divorced | 32 | 15.2 | 15.5 |
| Widowed | 10 | 4.8 | 4.8 |
| Never_Married | 28 | 13.3 | 13.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 3 | 1.4 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 219 | 69.5 | 71.1 |
| Separated | 7 | 2.2 | 2.3 |
| Divorced | 47 | 14.9 | 15.3 |
| Widowed | 11 | 3.5 | 3.6 |
| Never_Married | 24 | 7.6 | 7.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 7 | 2.2 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 175 | 49.2 | 50.4 |
| Separated | 15 | 4.2 | 4.3 |
| Divorced | 69 | 19.4 | 19.9 |
| Widowed | 23 | 6.5 | 6.6 |
| Never_Married | 65 | 18.3 | 18.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 2.5 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 350 | 59.8 | 60.8 |
| Separated | 32 | 5.5 | 5.6 |
| Divorced | 110 | 18.8 | 19.1 |
| Widowed | 42 | 7.2 | 7.3 |
| Never_Married | 42 | 7.2 | 7.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 9 | 1.5 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 1169 | 66.6 | 68.6 |
| Separated | 55 | 3.1 | 3.2 |
| Divorced | 241 | 13.7 | 14.1 |
| Widowed | 109 | 6.2 | 6.4 |
| Never_Married | 129 | 7.4 | 7.6 |
| Scantron_Error | 2 | 0.1 | 0.1 |
| NA | 49 | 2.8 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$g1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "g1")
| n | % | val% | |
|---|---|---|---|
| Married_partner | 7 | 43.8 | 46.7 |
| Separated | 0 | 0.0 | 0.0 |
| Divorced | 6 | 37.5 | 40.0 |
| Widowed | 1 | 6.2 | 6.7 |
| Never_Married | 1 | 6.2 | 6.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
g2_1 <- as.factor(d[,"g2_1"])
levels(g2_1) <- list(Live_alone="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g2_1)
new.d <- apply_labels(new.d, g2_1 = "Live alone")
temp.d <- data.frame (new.d, g2_1)
result<-questionr::freq(temp.d$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 765 | 21.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2792 | 78.5 | NA |
| Total | 3557 | 100.0 | 100 |
g2_2 <- as.factor(d[,"g2_2"])
levels(g2_2) <- list(spouse_partner="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g2_2)
new.d <- apply_labels(new.d, g2_2 = "A spouse or partner")
temp.d <- data.frame (new.d, g2_2)
result<-questionr::freq(temp.d$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 2309 | 64.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1248 | 35.1 | NA |
| Total | 3557 | 100.0 | 100 |
g2_3 <- as.factor(d[,"g2_3"])
levels(g2_3) <- list(Other_family="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g2_3)
new.d <- apply_labels(new.d, g2_3 = "Other family")
temp.d <- data.frame (new.d, g2_3)
result<-questionr::freq(temp.d$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 487 | 13.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3070 | 86.3 | NA |
| Total | 3557 | 100.0 | 100 |
g2_4 <- as.factor(d[,"g2_4"])
levels(g2_4) <- list(Other_non_family="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g2_4)
new.d <- apply_labels(new.d, g2_4 = "Other people (non-family)")
temp.d <- data.frame (new.d, g2_4)
result<-questionr::freq(temp.d$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 78 | 2.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3479 | 97.8 | NA |
| Total | 3557 | 100.0 | 100 |
g2_5 <- as.factor(d[,"g2_5"])
levels(g2_5) <- list(Pets="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g2_5)
new.d <- apply_labels(new.d, g2_5 = "Pets")
temp.d <- data.frame (new.d, g2_5)
result<-questionr::freq(temp.d$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 199 | 5.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3358 | 94.4 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 83 | 25.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 238 | 74.1 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 193 | 60.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 128 | 39.9 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 64 | 19.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 257 | 80.1 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 8 | 2.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 313 | 97.5 | NA |
| Total | 321 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 22 | 6.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 299 | 93.1 | NA |
| Total | 321 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 41 | 19.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 169 | 80.5 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 134 | 63.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 76 | 36.2 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 44 | 21 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 166 | 79 | NA |
| Total | 210 | 100 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 9 | 4.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 201 | 95.7 | NA |
| Total | 210 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 17 | 8.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 193 | 91.9 | NA |
| Total | 210 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 43 | 13.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 272 | 86.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 227 | 72.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 88 | 27.9 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 43 | 13.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 272 | 86.3 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 13 | 4.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 302 | 95.9 | NA |
| Total | 315 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 27 | 8.6 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 288 | 91.4 | NA |
| Total | 315 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 99 | 27.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 257 | 72.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 195 | 54.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 161 | 45.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 56 | 15.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 300 | 84.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 13 | 3.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 343 | 96.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 23 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 333 | 93.5 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 99 | 27.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 257 | 72.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 195 | 54.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 161 | 45.2 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 56 | 15.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 300 | 84.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 13 | 3.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 343 | 96.3 | NA |
| Total | 356 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 23 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 333 | 93.5 | NA |
| Total | 356 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 335 | 19.1 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1419 | 80.9 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 1188 | 67.7 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 566 | 32.3 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 220 | 12.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1534 | 87.5 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 32 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1722 | 98.2 | NA |
| Total | 1754 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 84 | 4.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1670 | 95.2 | NA |
| Total | 1754 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$g2_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_1: Live alone")
| n | % | val% | |
|---|---|---|---|
| Live_alone | 7 | 43.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 9 | 56.2 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_2: A spouse or partner")
| n | % | val% | |
|---|---|---|---|
| spouse_partner | 8 | 50 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 8 | 50 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$g2_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_3: Other family")
| n | % | val% | |
|---|---|---|---|
| Other_family | 1 | 6.2 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 15 | 93.8 | NA |
| Total | 16 | 100.0 | 100 |
result<-questionr::freq(temp.dd$g2_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_4: Other people (non-family)")
| n | % | val% | |
|---|---|---|---|
| Other_non_family | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
result<-questionr::freq(temp.dd$g2_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g2_5: Pets")
| n | % | val% | |
|---|---|---|---|
| Pets | 0 | 0 | NaN |
| Scantron_Error | 0 | 0 | NaN |
| NA | 16 | 100 | NA |
| Total | 16 | 100 | 100 |
rm(temp.dd)
g3 <- as.factor(d[,"g3"])
levels(g3) <- list(heterosexual="1",
Bisexual="2",
homosexual="3",
Other="4",
Prefer_not_to_answer="99",
Scantron_Error="*")
g3 <- ordered(g3, c("heterosexual","Bisexual","homosexual","Other","Prefer_not_to_answer","Scantron_Error"))
new.d <- data.frame(new.d, g3)
new.d <- apply_labels(new.d, g3 = "identify yourself")
temp.d <- data.frame (new.d, g3)
result<-questionr::freq(temp.d$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 3257 | 91.6 | 95.2 |
| Bisexual | 22 | 0.6 | 0.6 |
| homosexual | 54 | 1.5 | 1.6 |
| Other | 22 | 0.6 | 0.6 |
| Prefer_not_to_answer | 66 | 1.9 | 1.9 |
| Scantron_Error | 1 | 0.0 | 0.0 |
| NA | 135 | 3.8 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 302 | 94.1 | 94.7 |
| Bisexual | 2 | 0.6 | 0.6 |
| homosexual | 8 | 2.5 | 2.5 |
| Other | 1 | 0.3 | 0.3 |
| Prefer_not_to_answer | 5 | 1.6 | 1.6 |
| Scantron_Error | 1 | 0.3 | 0.3 |
| NA | 2 | 0.6 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 189 | 90.0 | 91.7 |
| Bisexual | 2 | 1.0 | 1.0 |
| homosexual | 11 | 5.2 | 5.3 |
| Other | 1 | 0.5 | 0.5 |
| Prefer_not_to_answer | 3 | 1.4 | 1.5 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 289 | 91.7 | 95.1 |
| Bisexual | 5 | 1.6 | 1.6 |
| homosexual | 6 | 1.9 | 2.0 |
| Other | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 4 | 1.3 | 1.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 327 | 91.9 | 96.5 |
| Bisexual | 1 | 0.3 | 0.3 |
| homosexual | 5 | 1.4 | 1.5 |
| Other | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 6 | 1.7 | 1.8 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 17 | 4.8 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 534 | 91.3 | 95.2 |
| Bisexual | 3 | 0.5 | 0.5 |
| homosexual | 5 | 0.9 | 0.9 |
| Other | 8 | 1.4 | 1.4 |
| Prefer_not_to_answer | 11 | 1.9 | 2.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 24 | 4.1 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 1603 | 91.4 | 95.5 |
| Bisexual | 8 | 0.5 | 0.5 |
| homosexual | 18 | 1.0 | 1.1 |
| Other | 12 | 0.7 | 0.7 |
| Prefer_not_to_answer | 37 | 2.1 | 2.2 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 76 | 4.3 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$g3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g3")
| n | % | val% | |
|---|---|---|---|
| heterosexual | 13 | 81.2 | 86.7 |
| Bisexual | 1 | 6.2 | 6.7 |
| homosexual | 1 | 6.2 | 6.7 |
| Other | 0 | 0.0 | 0.0 |
| Prefer_not_to_answer | 0 | 0.0 | 0.0 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 1 | 6.2 | NA |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
g4a <- as.factor(d[,"g4a"])
levels(g4a) <- list(Grade_school_or_less="1",
Some_high_school="2",
High_school_graduate_GED="3",
Vocational_school="4",
Some_college="5",
Associate_degree="6",
College_graduate="7",
Some_graduate_education="8",
Graduate_degree="9",
Scantron_Error="*")
g4a <- ordered(g4a, c("Grade_school_or_less","Some_high_school","High_school_graduate_GED","Vocational_school","Some_college","Associate_degree","College_graduate","Some_graduate_education","Graduate_degree","Scantron_Error"))
new.d <- data.frame(new.d, g4a)
new.d <- apply_labels(new.d, g4a = "education")
temp.d <- data.frame (new.d, g4a)
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
g4b <- as.factor(d[,"g4b"])
levels(g4b) <- list(Grade_school_or_less="1",
Some_high_school="2",
High_school_graduate_GED="3",
Vocational_school="4",
Some_college="5",
Associate_degree="6",
College_graduate="7",
Some_graduate_education="8",
Graduate_degree="9",
Dont_know="88",
Scantron_Error="*")
g4b <- ordered(g4b, c("Grade_school_or_less","Some_high_school","High_school_graduate_GED","Vocational_school","Some_college","Associate_degree","College_graduate","Some_graduate_education","Graduate_degree","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, g4b)
new.d <- apply_labels(new.d, g4b = "education-father")
temp.d <- data.frame (new.d, g4b)
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
g4c <- as.factor(d[,"g4c"])
levels(g4c) <- list(Grade_school_or_less="1",
Some_high_school="2",
High_school_graduate_GED="3",
Vocational_school="4",
Some_college="5",
Associate_degree="6",
College_graduate="7",
Some_graduate_education="8",
Graduate_degree="9",
Dont_know="88",
Scantron_Error="*")
g4c <- ordered(g4c, c("Grade_school_or_less","Some_high_school","High_school_graduate_GED","Vocational_school","Some_college","Associate_degree","College_graduate","Some_graduate_education","Graduate_degree","Dont_know","Scantron_Error"))
new.d <- data.frame(new.d, g4c)
new.d <- apply_labels(new.d, g4c = "education-mother")
temp.d <- data.frame (new.d, g4c)
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.d$g4a,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4a: You")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 100 | 2.8 | 3.1 |
| Some_high_school | 259 | 7.3 | 8.1 |
| High_school_graduate_GED | 793 | 22.3 | 24.7 |
| Vocational_school | 116 | 3.3 | 3.6 |
| Some_college | 704 | 19.8 | 21.9 |
| Associate_degree | 278 | 7.8 | 8.7 |
| College_graduate | 426 | 12.0 | 13.3 |
| Some_graduate_education | 96 | 2.7 | 3.0 |
| Graduate_degree | 441 | 12.4 | 13.7 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 344 | 9.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4b,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4b: Your father")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 849 | 23.9 | 27.2 |
| Some_high_school | 446 | 12.5 | 14.3 |
| High_school_graduate_GED | 652 | 18.3 | 20.9 |
| Vocational_school | 88 | 2.5 | 2.8 |
| Some_college | 111 | 3.1 | 3.5 |
| Associate_degree | 51 | 1.4 | 1.6 |
| College_graduate | 103 | 2.9 | 3.3 |
| Some_graduate_education | 18 | 0.5 | 0.6 |
| Graduate_degree | 81 | 2.3 | 2.6 |
| Dont_know | 728 | 20.5 | 23.3 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 430 | 12.1 | NA |
| Total | 3557 | 100.0 | 100.0 |
result<-questionr::freq(temp.d$g4c,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g4c: Your mother")
| n | % | val% | |
|---|---|---|---|
| Grade_school_or_less | 597 | 16.8 | 19.0 |
| Some_high_school | 500 | 14.1 | 15.9 |
| High_school_graduate_GED | 893 | 25.1 | 28.4 |
| Vocational_school | 120 | 3.4 | 3.8 |
| Some_college | 164 | 4.6 | 5.2 |
| Associate_degree | 100 | 2.8 | 3.2 |
| College_graduate | 156 | 4.4 | 5.0 |
| Some_graduate_education | 22 | 0.6 | 0.7 |
| Graduate_degree | 99 | 2.8 | 3.2 |
| Dont_know | 490 | 13.8 | 15.6 |
| Scantron_Error | 0 | 0.0 | 0.0 |
| NA | 416 | 11.7 | NA |
| Total | 3557 | 100.0 | 100.0 |
rm(temp.dd)
g5 <- as.factor(d[,"g5"])
levels(g5) <- list(full_time="1",
part_time="2",
unemployed="3",
Retired="4",
disability_permanently="5",
disability_for_a_time="6",
Volunteer_work="7",
Other="8",
Scantron_Error="*")
g5 <- ordered(g5, c("full_time","part_time","unemployed","Retired","disability_permanently","disability_for_a_time", "Volunteer_work","Other","Scantron_Error"))
new.d <- data.frame(new.d, g5)
new.d <- apply_labels(new.d, g5 = "job")
temp.d <- data.frame (new.d, g5)
result<-questionr::freq(temp.d$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 880 | 24.7 | 25.7 |
| part_time | 197 | 5.5 | 5.7 |
| unemployed | 58 | 1.6 | 1.7 |
| Retired | 1629 | 45.8 | 47.5 |
| disability_permanently | 456 | 12.8 | 13.3 |
| disability_for_a_time | 36 | 1.0 | 1.1 |
| Volunteer_work | 13 | 0.4 | 0.4 |
| Other | 69 | 1.9 | 2.0 |
| Scantron_Error | 90 | 2.5 | 2.6 |
| NA | 129 | 3.6 | NA |
| Total | 3557 | 100.0 | 100.0 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 89 | 27.7 | 28.3 |
| part_time | 25 | 7.8 | 7.9 |
| unemployed | 9 | 2.8 | 2.9 |
| Retired | 145 | 45.2 | 46.0 |
| disability_permanently | 30 | 9.3 | 9.5 |
| disability_for_a_time | 5 | 1.6 | 1.6 |
| Volunteer_work | 0 | 0.0 | 0.0 |
| Other | 7 | 2.2 | 2.2 |
| Scantron_Error | 5 | 1.6 | 1.6 |
| NA | 6 | 1.9 | NA |
| Total | 321 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 72 | 34.3 | 35.0 |
| part_time | 11 | 5.2 | 5.3 |
| unemployed | 1 | 0.5 | 0.5 |
| Retired | 91 | 43.3 | 44.2 |
| disability_permanently | 20 | 9.5 | 9.7 |
| disability_for_a_time | 2 | 1.0 | 1.0 |
| Volunteer_work | 1 | 0.5 | 0.5 |
| Other | 3 | 1.4 | 1.5 |
| Scantron_Error | 5 | 2.4 | 2.4 |
| NA | 4 | 1.9 | NA |
| Total | 210 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 94 | 29.8 | 30.9 |
| part_time | 18 | 5.7 | 5.9 |
| unemployed | 7 | 2.2 | 2.3 |
| Retired | 140 | 44.4 | 46.1 |
| disability_permanently | 24 | 7.6 | 7.9 |
| disability_for_a_time | 4 | 1.3 | 1.3 |
| Volunteer_work | 2 | 0.6 | 0.7 |
| Other | 11 | 3.5 | 3.6 |
| Scantron_Error | 4 | 1.3 | 1.3 |
| NA | 11 | 3.5 | NA |
| Total | 315 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 49 | 13.8 | 14.4 |
| part_time | 18 | 5.1 | 5.3 |
| unemployed | 8 | 2.2 | 2.3 |
| Retired | 167 | 46.9 | 49.0 |
| disability_permanently | 75 | 21.1 | 22.0 |
| disability_for_a_time | 5 | 1.4 | 1.5 |
| Volunteer_work | 2 | 0.6 | 0.6 |
| Other | 11 | 3.1 | 3.2 |
| Scantron_Error | 6 | 1.7 | 1.8 |
| NA | 15 | 4.2 | NA |
| Total | 356 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 130 | 22.2 | 23.0 |
| part_time | 30 | 5.1 | 5.3 |
| unemployed | 9 | 1.5 | 1.6 |
| Retired | 278 | 47.5 | 49.1 |
| disability_permanently | 86 | 14.7 | 15.2 |
| disability_for_a_time | 4 | 0.7 | 0.7 |
| Volunteer_work | 3 | 0.5 | 0.5 |
| Other | 9 | 1.5 | 1.6 |
| Scantron_Error | 17 | 2.9 | 3.0 |
| NA | 19 | 3.2 | NA |
| Total | 585 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 441 | 25.1 | 26.2 |
| part_time | 94 | 5.4 | 5.6 |
| unemployed | 24 | 1.4 | 1.4 |
| Retired | 802 | 45.7 | 47.7 |
| disability_permanently | 219 | 12.5 | 13.0 |
| disability_for_a_time | 15 | 0.9 | 0.9 |
| Volunteer_work | 5 | 0.3 | 0.3 |
| Other | 28 | 1.6 | 1.7 |
| Scantron_Error | 52 | 3.0 | 3.1 |
| NA | 74 | 4.2 | NA |
| Total | 1754 | 100.0 | 100.0 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.dd$g5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = " g5")
| n | % | val% | |
|---|---|---|---|
| full_time | 5 | 31.2 | 31.2 |
| part_time | 1 | 6.2 | 6.2 |
| unemployed | 0 | 0.0 | 0.0 |
| Retired | 6 | 37.5 | 37.5 |
| disability_permanently | 2 | 12.5 | 12.5 |
| disability_for_a_time | 1 | 6.2 | 6.2 |
| Volunteer_work | 0 | 0.0 | 0.0 |
| Other | 0 | 0.0 | 0.0 |
| Scantron_Error | 1 | 6.2 | 6.2 |
| Total | 16 | 100.0 | 100.0 |
rm(temp.dd)
g6_1 <- as.factor(d[,"g6_1"])
levels(g6_1) <- list(Insurance_employer="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_1)
new.d <- apply_labels(new.d, g6_1 = "Insurance_employer")
temp.d <- data.frame (new.d, g6_1)
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
g6_2 <- as.factor(d[,"g6_2"])
levels(g6_2) <- list(Insurance_family="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_2)
new.d <- apply_labels(new.d, g6_2 = "Insurance_family")
temp.d <- data.frame (new.d, g6_2)
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
g6_3 <- as.factor(d[,"g6_3"])
levels(g6_3) <- list(Insurance_insurance_company="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_3)
new.d <- apply_labels(new.d, g6_3 = "Insurance_insurance_company")
temp.d <- data.frame (new.d, g6_3)
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
g6_4 <- as.factor(d[,"g6_4"])
levels(g6_4) <- list(Insurance_exchange="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_4)
new.d <- apply_labels(new.d, g6_4 = "Insurance_exchange")
temp.d <- data.frame (new.d, g6_4)
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
g6_5 <- as.factor(d[,"g6_5"])
levels(g6_5) <- list(Medicaid_state="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_5)
new.d <- apply_labels(new.d, g6_5 = "Medicaid_state")
temp.d <- data.frame (new.d, g6_5)
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
g6_6 <- as.factor(d[,"g6_6"])
levels(g6_6) <- list(Medicare_government="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_6)
new.d <- apply_labels(new.d, g6_6 = "Medicare_government")
temp.d <- data.frame (new.d, g6_6)
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
g6_7 <- as.factor(d[,"g6_7"])
levels(g6_7) <- list(VA_Military="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_7)
new.d <- apply_labels(new.d, g6_7 = "VA_Military")
temp.d <- data.frame (new.d, g6_7)
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
g6_8 <- as.factor(d[,"g6_8"])
levels(g6_8) <- list(Do_not_have="1",
Scantron_Error="*")
new.d <- data.frame(new.d, g6_8)
new.d <- apply_labels(new.d, g6_8 = "Do_not_have")
temp.d <- data.frame (new.d, g6_8)
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
temp.dd <- new.d[which(new.d$siteid == "Los Angeles County.80"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Northern CA.30"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Greater CA.10"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Detroit.60"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Louisiana.40"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Georgia.20"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)
temp.dd <- new.d[which(new.d$siteid == "Michigan.61"), ]
result<-questionr::freq(temp.d$g6_1,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided through my current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_employer | 1202 | 33.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2355 | 66.2 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_2,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance provided by another family member (e.g., spouse) through their current or former employer or union (including Kaiser/HMO/PPO)")
| n | % | val% | |
|---|---|---|---|
| Insurance_family | 371 | 10.4 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3186 | 89.6 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_3,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased directly from an insurance company (by you or another family member)")
| n | % | val% | |
|---|---|---|---|
| Insurance_insurance_company | 232 | 6.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3325 | 93.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_4,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Insurance purchased from an exchange (sometimes called Obamacare or the Affordable Care Act)")
| n | % | val% | |
|---|---|---|---|
| Insurance_exchange | 105 | 3 | 100 |
| Scantron_Error | 0 | 0 | 0 |
| NA | 3452 | 97 | NA |
| Total | 3557 | 100 | 100 |
result<-questionr::freq(temp.d$g6_5,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicaid or other state provided insurance")
| n | % | val% | |
|---|---|---|---|
| Medicaid_state | 510 | 14.3 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3047 | 85.7 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_6,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "Medicare/government insurance")
| n | % | val% | |
|---|---|---|---|
| Medicare_government | 1620 | 45.5 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 1937 | 54.5 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_7,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "VA/Military Facility (including those who have ever used or enrolled for VA health care)")
| n | % | val% | |
|---|---|---|---|
| VA_Military | 601 | 16.9 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 2956 | 83.1 | NA |
| Total | 3557 | 100.0 | 100 |
result<-questionr::freq(temp.d$g6_8,total = TRUE)
kable(result, format = "simple", align = 'l', caption = "I do not have any medical insurance")
| n | % | val% | |
|---|---|---|---|
| Do_not_have | 63 | 1.8 | 100 |
| Scantron_Error | 0 | 0.0 | 0 |
| NA | 3494 | 98.2 | NA |
| Total | 3557 | 100.0 | 100 |
rm(temp.dd)